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To the World: We are open! all the customer, staff, family in Miyagi Guest House is safe, the tragedy did not interfere our life that much, but it takes time to be normal.
A newly-built guest house opened on August 1, 2011. The first guesthouse with a bar space in Sendai. Conv
Find a Sendai, Japan hostel and save money on discount lodging. Hosteling in Sendai, Japan offers a different travel experience than staying at traditional accommodations. Youth hostels allow you to meet new people and learn from other international and worldly travelers. Most hostels are conveniently located in the center of the action close to public transportation, including buses and rails. Staying at a Sendai, Japan hostel is a great option whether you are backpacking or traveling on a budget . Browse our hostels and plan your Sendai, Japan vacation today!


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Huesman completed a season-high 22 passes for 229 yards as Chattanooga lost at No. 13 Wofford in overtime, 16-13. Huesman completed nine of 10 passes for 90 yards on third down and converted them into seven first downs. The Chattanooga, Tenn., native added 68 yards rushing on 24 carries and caught one pass for five yards.
Trailing 10-3 in the fourth quarter, Huesman engineered an 18-play, 72-yard drive that culminated with a Kendrix Huitt touchdown run to pull the Mocs even and force overtime. It was the Mocs longest scoring drive, in terms of plays, since 2009. The freshman converted four third downs on the drive with two coming on the ground and two through pass completions.
Huesman has already set a UTC freshman record for pass completions (154) and attempts (231). He needs 166 yards to break the rookie record for passing yards, set by Kenyon Earl (1,643) in 1991. His 11 TD passes are also two shy of Earl's freshman record. Huesman leads all SoCon freshman in rushing (79.5 yds/game), rushing TDs (6), pass efficiency (131.8), passing TDs (11) and is third in the league overall in total offense (227.3 yds/game).
The Mocs (5-5, 4-3 SoCon) host Elon (3-7, 1-6 SoCon) for the regular season finale on Saturday, Nov. 17. Kickoff is set for 2:00 p.m. (E.S.T.) at Finley Stadium. It is Senior Day for the Mocs as well as Military Appreciation Day. Free Admission is available to all service men and women with a valid military ID. Tickets are available on GoMocs.com or by calling the UTC Ticket Office at (423) 266-MOCS (6627).

subset: commoncrawl


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|Significant Downturn in Nonresidential Construction Activity Projected through 2010
|Monday, 13 July 2009 07:21
Feeling the effects of the struggling overall U.S. economy, nonresidential construction spending is expected to decrease by 16 percent in 2009 and drop by another almost 12 percent in 2010 in inflation adjusted terms. Commercial projects will see the most significant decrease in activity. In contrast, most institutional building categories are expected to see much more modest declines over this period. These are highlights from the American Institute of Architects (AIA) semi-annual Consensus Construction Forecast, a survey of the nation's leading construction forecasters.
Market Segment Consensus Growth Forecasts
"This nonresidential downturn is shaping up to be the deepest decline in nonresidential activity in over a generation." Baker added. "However, we're beginning to see some moderation in the trends in design billings at architecture firms, so we hopefully are nearing the bottom of this cycle."
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Lane Cake
Lane Cake: now there's a tall southern belle of a layer cake, filled with coconut, chopped fruit and nuts and a generous serving of whiskey or brandy, and topped off with a snowy range of fluffy frosting. Cutting into this cake is particularly enjoyable: the white frosting gives way to a creamy-colored cake, with a slightly more yellow-toned custard, flecked with a confetti of nuts and fruits contained therein. More


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Bono's a busy man. After guest editing the new issue of Vanity Fair, Bono trekked off to the Northern African nation of Morocco to join his bandmates, as well as The Unforgettable Fire producer Brian Eno, for a songwriting session. Whether any album is forthcoming from the sessions remains to be seen: "We have no plans for the music yet," Bono reported on the band's website.
Apparently no one's more psyched than President George Bush, who after delivering a speech Thursday at the G-8 summit, allegedly shouted to an aid "Where's Bono? Bono for President!" Bush then pulled out his copy of Zooropa, hoping for an autograph.


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Ferdinand, Indiana Pet Friendly Hotels & Lodging
United States » Indiana » Ferdinand
Looking for a hotel in Ferdinand, IN that you can bring your pet to? We made sure that each one of the hotels below are pet friendly, so you can enjoy your trip with your pet by your side! Once you have found a pet friendly hotel, you can book your stay instantly from our website or call 866-212-1803 to speak with a pet travel agent.
Browse Pet Friendly Hotels In Ferdinand, Indiana
Rates from
440 South Main St - Ferdinand, IN (Map)
Located in Ferdinand, Ferdinand Inn is within the region of Holiday World and Splashin' Safari and Lincoln Boyhood National Memorial. This hotel is within the region of Lincoln Amphitheatre....
Overview | Pet Policy | Map


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I don't think you'll have to get back the original MIOS if the new DIOS MIOS allows retail play. That way, even if you don't want to use USB backups, you can still play from the disc channel.
I don't think your GC backup MIOS is interfering. When you install DIOS MIOS it overwrites any custom mIOS.


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When you come to Shine, like all close friends & family, you will be coming in the back door! The building is 727 E. Jefferson St.; however, our parking lot sits at the back of the building, so we use the back doors. Drive to the parking lot of 732 E. Market (The Green Building) between Shelby & Clay and cross the alley to the back of the parking lot to Shine (in the little green building!)
Enter the first floor for all Music & Movement classes.
Please make an effort to be on time for your class. If it is your first visit to Shine, please arrive 15 minutes early to fill out paperwork and explore the space - view the art and meet some great friends. Before your first class, you will need to fill out a waiver but also please make your teacher aware of any injuries or health problems you may have.
There are shelves available for personal belongings: shoes, phones (please turn off ringer!), bags, keys, etc. We will lock the door at the start of class to ensure the safety of your personal belongings.
Only bring things onto the studio floor that are needed for class: mats for yoga, towels, and water. You are welcome to use one of our mats if you do not have one.
We prefer that no shoes go into the studio during class times.
We are a teaching/learning community. Feel free to ask your teacher questions about your practice.


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Crazy Hills of Europe (CHoE) is a crew born in France in 2008, of pure downhill freeborders in the search for the best hills of Europe, and trying to produce the sickest Freebord videos.
Freebording is not snowboarding or skateboarding. Our boards allow us to carve, slide, control our speed and spin just like on a snowboard, except we are on the road.
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INDIANAPOLIS — Some key state senators are stalling a bill that would make Amazon.com and other online-only retailers start collecting Indiana's 7 percent sales tax this summer.
The Indiana House voted overwhelmingly last month in favor of requiring online sales tax collection in July, six months earlier than under a deal then-Gov. Mitch Daniels brokered with Amazon last year.
Senate Appropriations Committee chairman Luke Kenley says his committee won't take up the bill and that the state should abide by the Amazon agreement.
Kenley says he understands the frustrations of traditional retailers over the price disadvantage, but that Congress first needs to give states more authority on collecting taxes from online businesses.
The Indiana Retail Council plans to keep pushing the issue through the end of the legislative session in late April.


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Barry Newstead, the Wikimedia Foundation's Chief Global Development Officer talks at the first Wikipedia in Higher Education Summit in Boston about how the new Wikipedia University Program fits into the Wikimedia Foundation's Global Development strategy (Simmons College, Boston, July 9, 2011)
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Photos and Review by Oyster.com Investigators
An exclusive hotel catering to business travelers and featuring sexy, highly stylized decor.
With creative lighting, highly stylized furniture, a constant techno soundtrack, and a candle scent developed exclusively for the hotel -- the W chain cares greatly about the mood it creates. But this isn't quite a designer boutique. It's a member of the Starwood hotel family, and a stylish sister to the Westins and Sheratons the world over. But the W brand tries hard to distance itself from the rest. It even has its own language -- the lobby is the "living room," elevators are "lifts" and the gym is simply "Sweat." For all this sexy gleam, the hotel manages to get away with charging more than twice as much as the Intercontinental right across the street.
What's interesting about this is that the W New York primarily caters to business travelers -- this is made clear by the constant presence of Blackberries and briefcases throughout the cozy "living room." The lobby is undeniably inviting and cozy (particularly with its fireplace), and the modern, stylish rooms feel less sterile than a typical room in a large hotel chain.
The chain's affiliation with Starwood brands and its popular guest loyalty program make it an attractive option for business travelers, particularly since there aren't any other Starwood hotels in Midtown East (except the small but ultra high-end St. Regis). As the first W to open (in 1998), and having been renovated in the fall of 2008 and then again in 2012 (event spaces only), it's the brand's New York flagship. All W Hotels are "80 percent brand and 20 percent indigenous," meaning New York hotels feature different design influences than the W in South Beach, or Marrakech.
In Midtown East, a 15-20 minute walk from Central Park, and surrounded by office buildings and restaurants. But there's not much nightlife in the area.
The W New York is located in Midtown East, a neighborhood that has long been a favorite for visitors who come to the city for both work and play. Though the immediate blocks surrounding the hotel feel like a "hotel district," business travelers love the area because it is convenient to the offices of nearly every Fortune 500 company, and is just six blocks from Grand Central, which services all East Side subway lines.
Leisure guests enjoy the central location of the hotel, which is convenient to popular tourist destinations, including Radio City Music Hall, Rockefeller Center, and the MoMA -- all are within a two-to-six block radius. Other areas of interest nearby include Central Park, an 843-acre haven for the urban outdoorsman just 20 blocks north of the hotel. The hotel has hosted several high-profile guests in town to visit to the U.N., which is just five blocks away.
The Theater District and the lights and crowds of Times Square are just a 10- to 15-minute walk to the west.
The hotel is also convenient to Lexington Avenue shopping, which includes favorites like Bloomingdales, as well as the more upscale shops of Madison and Fifth avenues like Chanel, Prada, and Dolce & Gabbana, and high-end department stores such as Saks Fifth Avenue and Barney's.
The hotels is just two to six blocks away from nearly every east side subway line, and it's easy to head west, via the 42nd Street subway shuttle.
Most of the midtown neighborhood is considerably less empty in the evenings and late at night. Still, because there are so many higher end hotels in the immediate area -- with doormen loitering out front -- safety shouldn't be a huge concern for guests.
About 30 to 90 minutes from three airports.
New York has three nearby airports: JFK, La Guardia, and Newark (in New Jersey). Flying into JFK or La Guardia is typically easiest and the least time consuming. From JFK, it's a flat-rate $45 (one-hour) taxi to anywhere in Manhattan. From La Guardia, it's about a $40 (30-minute) metered cab ride to midtown Manhattan. Rides from Newark cost at least $40 (plus tolls) and can take over one-and-a-half hours. Don't forget to tip your driver 15 to 25 percent.
To save some cash, group shuttles are available at all three airports for about $14 per person. For more information on the shuttles, go to Super Shuttle or New York Airport Service. You can also take public transit from any of the airports for as little as $7 per person, but travel times can take up to two hours and involve a lot of lugging bags up and down stairs. For mass-transit directions right to the hotel, check out HopStop.com.
Some of the most modern, stylish rooms in Midtown East, with iPod docks and Bliss bath products, but the standard rooms are tiny, and the purple mood lighting can be too dim.
Rooms are decorated in a white and "aubergine" color palette, and have textured purple wallpaper in the bathroom, a purple orb light near the bed, a sleek purple cordless phone, and a purple chenille desk chair. The desk, slim closet, and minibar are all made of modern dark wood that the hotel touts as "exotic zebrawood."
Spa Suites are adjacent to the spa, Bliss49 and the fitness center. The open-plan bathroom essentially flows into the living area, so that the tub sits right behind the couch with a great view of the television. The shower is also open and located off the living room.
The hotel has two top-of-the-line Extreme Wow Suites, which the manager said can go for $4,000 "on a good night." Celebrities like Snoop Dogg and Terrence Howard have stayed in the suites, which feature beautiful wraparound terraces (including waterproof pool tables), Bose speaker systems built-in to the walls with iPod and XM Satellite radio integration, enormous flat-screen TVs, and another TV built into the bathroom mirror.
The spa, fitness center, and business facilities are all fantastic; the ground floor shopping options are impressive but dangerously expensive!
A Mega Room is spacious enough to hold a cot, and the neighborhood is filled with a variety of cheap, family-friendly eating options. Service at the hotel is so friendly and accommodating that I don't doubt they'd do their best to enhance a child's stay.
Cats and dogs less than 40 pounds are welcome, but guests must pay an additional per day fee, as well as a non-refundable cleaning fee.
The W's P.A.W. (Pets Are Welcome) program offers perks like dog walking, grooming, and special pet-friendly snacks. There's even a pets' room service menu. The only issue is that there's nary a park or patch of green space within five avenue blocks of the hotel (about a 15- to 20-minute walk to Central Park).
The W New York has a few casualy restaurants, but Midtown East is filled with eating options.
Heartbeat serves breakfast daily, and serves cocktails in the evening.
The W Cafe serves breakfast daily, and transforms into Oasis Bar in the evenings for cocktails and light fare.
Whiskey Blue is a stylish lounge, open every evening.
Lexington Avenue is clogged with hotels and office buildings, but a block over on Third Avenue there are lots of chain restaurants (plus my all-time favorite New York bagel place, Ess-a-Bagel). Second Avenue is lined with great restaurants.
Lobby bar Oasis is relaxed and almost always buzzing. Whiskey Blue, also on site, is the trendiest bar in the neighborhood.
The hotel is also connected to two bars. Oasis Bar is located in the middle of the lobby, and is a popular spot for meetings and casual after-work gatherings, particularly given the lobby's cozy atmosphere replete with comfy couches and a fireplace.
Whiskey Blue is adjacent to the lobby, and is much more of a scene. The swank David Rockwell-designed space features expensive drinks, pictures of rock stars on the wall, and waitresses in tight black dresses. It's the most stylish bar in the area and is therefore a magnet for many business travelers.
Superb service -- not the food or the spaces -- makes this location stand apart.
Business (and some leisure) travelers craving style and a social scene will enjoy the colorful, 688-room flagship of the W chain amidst Midtown East's gray business hotels. Cutesy language and small, mood-lit rooms are not for everyone, but great service and a popular bar scene seem to justify the steep rates.
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The Quantified Self community is where quantified self enthusiasts can share experiences and success stories, using device and application tracking to gain insight into their health.
Pozole - Only a small amount of oil is needed to sauté meat.
2 pounds lean beef, cubed
1 Tbsp. olive oil
1 large onion, chopped
1 clove garlic, finely chopped
¼ tsp. salt
1/8 tsp. pepper
¼ cup fresh cilantro, chopped
1 can (15 ounces) stewed tomatoes
2 ounces tomato paste
1 can (1 pound 13 ounces) hominy
• In a large pot, heat olive oil. Add beef and sauté.
• Add onion, garlic, salt, pepper, cilantro, and enough water to cover meat. Stir to mix ingredients evenly. Cover pot and cook over low heat until meat is tender.
• Add tomatoes and tomato paste. Continue cooking for about 20 minutes.
• Add hominy and continue cooking another 15 minutes, stirring occasionally. If too thick, add water for desired consistency.
Option: Skinless, boneless chicken breasts can be used instead of beef cubes.
Meat 3
Bread 1
Vegetable ½
Fat 1


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Open AccessThis article is
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- freely available
- re-usable
Entropy 2013, 15(10), 4520-4539; doi:10.3390/e15104520
3D Reconstruction of Coronal Loops by the Principal Component Analysis
Received: 24 August 2013 / Revised: 27 September 2013 / Accepted: 10 October 2013 / Published: 22 October 2013
(This article belongs to the Special Issue Advanced Signal Processing in Heliospheric Physics)
Download PDF [7780 KB, uploaded 24 February 2015]
AbstractKnowing the three dimensional structure of plasma filaments in the uppermost part of the solar atmosphere, known as coronal loops, and especially their length, is an important parameter in the wave-based diagnostics of this part of the Sun. The combination of observations of the Sun from different points of observations in space, thanks to the most recent missions, including the Solar Dynamics Observatory (SDO) and the Solar TErrestrial RElations Observatory (STEREO), allows us to infer information about the geometrical shape of coronal loops in 3D space. Here, we propose a new method to reconstruct the loop shape starting from stereoscopically determined 3D points, which sample the loop length, by principal component analysis. This method is shown to retrieve in an easy way the main parameters that define the loop, e.g., the minor and major axes, the loop plane, the azimuthal and inclination angles, for the special case of a coplanar loop.
Keywords: solar corona; coronal loop; 3D reconstruction
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Nisticò, G.; Verwichte, E.; Nakariakov, V.M. 3D Reconstruction of Coronal Loops by the Principal Component Analysis. Entropy 2013, 15, 4520-4539.View more citation formats
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Nisticò G, Verwichte E, Nakariakov VM. 3D Reconstruction of Coronal Loops by the Principal Component Analysis. Entropy. 2013; 15(10):4520-4539.Chicago/Turabian Style
Nisticò, Giuseppe; Verwichte, Erwin; Nakariakov, Valery M. 2013. "3D Reconstruction of Coronal Loops by the Principal Component Analysis." Entropy 15, no. 10: 4520-4539.
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Select a region below to explore Resorts & Lodges in that destination.
Plan your trip to Arizona
Select a region using the map to your left or pick one from the drop down below.
Casino - Resorts and Lodges in Arizona
Arizona invites you to try your luck with a host of gaming options. Harrah's Ak-Chin Casino Resort is a 40,000-square-foot gaming center featuring a host of options like fast-action slots, keno, poker, live dealer blackjack, and much more at your fingertips 24 hours a day. Hit the jackpot at Talking Stick Resort, which features more than 800 slot machines spread over 240,000 square feet. Hit it big in High Country, where Hon-Dah Resort Casino & Conference Center showcases a bevy of slot machines, blackjack tables, a poker room, and much more. Lodge at Cliff Castle keeps the games going with slots, poker, and blackjack. With so many gaming options, you're sure to find lady luck somewhere in Arizona!
Arizona Top List Picks
Top 10 Scottsdale Hotels
Sun-soaked mountains, views of gorgeous desert life, and the exciting city life are what await at your Scottsdale vacation. Whether you are planning to bring the whole family or spend some time with a... more
Top Grand Canyon Vacations
Soar over the canyons for a view from the clear blue skies. Dive down the rock and cruise over the tough terrain. Or, grab a paddle for some rough rafting down the Colorado River. It's all waiting... more
Top 10 Arizona Getaways
This one was easy: Arizona is so full of terrific places to visit, it's hard not to describe the entire state as one big vacation destination. Still, some places do stand out – the exquisite golf... more


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in this issue
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A Bright Future for US STEMs from Students' Love of Chemistry
12:59 PM MDT | June 9, 2011 | Katie Hunt, Dow Chemical
It's no secret that a fundamental understanding of science, technology, engineering and math (STEM) is essential to sustaining a global economy. We've been alerted by President Obama that America's 15-year-olds rank 21st in science and 25th in math compared to their peers around the world; but it doesn't have to be this way. With more than 90 percent of all manufactured products in the world touched by the power of chemistry, our industry is, and must continue to be, a positive force for change in the world. Today, the pressing challenge...
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The Sims Online was a game well before its time. It was a shame to see EA pull it from their servers back in August 2008, when it was re-branded earlier that year as EA Land. A number of fans still played the game when the doors closed, so it's to no surprise there is interest to re-create the game and to introduce it on private servers. That's the purpose of TSO Restoration. How does one reverse engineer EA's platform? The answer to that (and many other questions – including the legal aspects of the game) can be read from the following interview conducted by The Alphaville Herald:
Urizenus: How does one do something like this, especially now that the original TSO is no more? Do you reverse engineer EA's platform?
Ghost: Unfortunately, because the TSO servers are no longer online – we're unable to gather any more packets. This means we're no longer an "emulation" project. Everything except perhaps the art and graphics is being recreated by our team.
Urizenus: So you are building it from scratch. Will it be aesthetically identical to the tSO we remember?
Ghost: Yes, our goal of the project is to make it look and interact exactly as the original TSO.
Urizenus: So the same motives then. What about all the usual interactions? tickling, dancing etc?
Ghost: You will be able to do all of the interactions. In fact, there is no reason we can not have more than just the original interactions. Our team plans on not only providing the same TSO experience for free, but also adding improvements to the game. What is to stop us from supporting unicode with special characters? Why not raise the tile limit and have size nine or ten lots? These are just a few of the ideas our team has in making the game more enjoyable.
Urizenus: What about the possibility of having users provide custom content and custom animations?
Ghost: As we saw in EA-Land, the TSOClient definitely has the potential to support such endeavors. We will pursue such capabilities in the future. I can't promise you that custom content will be in our first release though.


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A state Senate committee moved to eliminate the automatic annual inflation increase, a provision in state statute that became a point of contention for university budget-writers and a pesky irritant for Gov. Rick Scott, who has stumped for no tuition hikes – period.
With Florida's economy strengthening, spending on higher education has risen. Last year, lawmakers gave back $300 million universities had to pull from reserves to get through the recession and tacked on $150 million in new university funding.
Scott insisted on no new tuition increases. The Legislature, with many leaders arguing that Florida universities are comparatively inexpensive, budgeted a 3 percent tuition hike, which Scott vetoed.
University presidents cited state law that requires them to invoke the inflation increase when tuition stays flat. It amounted to a 1.7 percent.


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Jeremiah's Heart Music is a ♦Solo Singer/Guitarist Act♦
that can enhance any celebration with
LIVE MUSIC and ENTERTAINMENT
We are still in the beginning stages of things but our
passion and love for music will take us far.
My goal is to make any event a bit more spectacular
by providing music and songs that truly
are sung from the heart. I live to
entertain and am so grateful that I have this
opportunity to do what I love the most.
"Everyday I'm learning, everyday I
grow a little better" ♥
I provide the sound equipment (PA system w/speaker,
microphone, etc) It's great for any occasion -from large
outdoor settings to small indoor settings.
Anniversaries, Banquets, Birthday Parties, Children's Birthday Parties, Sweet 16 Parties, Celebrations, Christmas Parties, , Cocktail Parties, Community Events, Conventions, Corporate Functions, Festivals, Fund Raisers, Funerals, Graduation Parties, Grand Openings, Picnics, Private Parties, Proms, Restaurants, Reunions, Weddings, Wedding Ceremonies, Wedding Receptions...and more.


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Drug Compare
1 2
- Basic Info
Generic: Ofirmev
It is used to treat pain and fever
What is this medicine?ACETAMINOPHEN (a set a MEE noe fen) is a pain reliever. It is used to treat pain and fever.
What should I tell my health care provider before I take this medicine?They need to know if you have any of these conditions:
How should I use this medicine?This medicine is for injection into a vein. It is given by a health care professional in a hospital or clinic setting.
Talk to your pediatrician regarding the use of this medicine in children. While this drug may be prescribed for children as young as 2 years old for selected conditions, precautions do apply.
Overdosage: If you think you've taken too much of this medicine contact a poison control center or emergency room at once.
What if I miss a dose?This does not apply.
What may interact with this medicine?
What should I watch for while using this medicine?Tell your doctor or healthcare professional if your symptoms do not start to get better or if they get worse.
Do not take other medicines that contain acetaminophen with this medicine. Too much acetaminophen can be very dangerous and cause an overdose. Always read labels carefully.
Report any possible overdose to your doctor right away, even if there are no symptoms. The effects of extra doses may not be seen for many days.
What side effects may I notice from receiving this medicine?Side effects that you should report to your doctor or health care professional as soon as possible:
Side effects that usually do not require medical attention (Report these to your doctor or health care professional if they continue or are bothersome.):
1 2
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More than 50,000 people go hungry every day in Houston, including 3,600 children. Their situations vary – some live at or below the poverty line, others earn too much to be considered impoverished and some are experiencing a temporary setback – but all are in need. Since 1982, the Houston Food Bank has worked to relieve hunger in Southeast Texas. It's the largest source of food for nearly 600 hunger relief agencies in 18 counties, including church food pantries, homeless shelters, safe havens for the battered and abused, and nutrition sites for children and the elderly.
For the past six years, Bank of America has supported the Houston Food Bank through grant funding, including an unrestricted Neighborhood Builders grant of $200,000 in 2011 and a $40,000 grant in 2013 to provide 120,000 meals to the Houston community. Every dollar donated to the Food Bank can provide nine meals. Knowing that, Bank of America matches individual donations through its Give a Meal program. The bank also matches Houston employees' donations to the Food Bank up to $5,000.
Hundreds of Bank of America employees also volunteer at the Houston Food Bank each year. Most recently, a group of 120 employees spent a December afternoon packing 2,340 boxes of food weighing 70,200 pounds – the equivalent of 58,500 meals. Beyond these efforts, Texas and Houston Market President Kim Ruth is serving her second year as co-chair of the Food Bank's board and chair of key fundraising events for the organization.
"Before Bank of America provides volunteer or financial support to an organization, we first look at the organization's impact," said Ruth. "The Houston Food Bank is a critical component of Houston and the Southeast Texas region." With support from companies like Bank of America, the Food Bank is entering its 32nd year and providing 64 million nutritious meals to more than 900,000 people annually.
Join the conversation: See how we're connecting with our customers, clients, and communities on the Bank of America Facebook page and on Twitter at @BofA_Community.


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Whether you have Down syndrome, know someone who does or just want to show your support, come and join us! At the Buddy Walk, you will join 5,000 walkers from all over central Ohio as we unite for a common cause and raise funds to support the Down Syndrome Association of Central Ohio (DSACO) and National Down Syndrome Society.
The Buddy Walk is more than a walk around Crew Stadium! Visit our vendors who specialize in providing goods or services to people with disabilities. Check out the interactive exhibits featuring kid-friendly activities. Many of our Buddy Walk sponsors will also be on hand to meet the families DSACO serves. Check out the raffle, photo booth, and other activities.


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Tuesday, August 4, 2015
Jammu Kashmir
Vohra discusses arrangements for JU hosting the 101st Indian Science Congress in 2014
Newspoint Bureau
Jammu Tawi, July 20
N N Vohra, Governor, chaired a high level meeting at the Raj Bhavan here today to discuss the arrangements to be put in place for the 101st Indian Science Congress being held at the University of Jammu from 3rd - 7th February 2014. The theme of this Science Congress is "Innovations in Science and Technology for Inclusive Development".
After earlier discussions with Prof R C Sobti, President of the Indian Science Congress Association, the Governor, who is Chancellor of the Jammu University, had invited the Vice Chancellors of all the 9 Universities in the State, Director SKIMS, Srinagar, Director, IIIM, Jammu, Director, NIT, Srinagar, Principals of Medical Colleges at Jammu and Srinagar, Principal of the College of Engineering and Technology, Jammu, and Director, Central Institute of Temperate Horticulture, Srinagar to this meeting.
The Governor impressed upon all the Vice Chancellors and the heads of the various medical, science and technology institutions of higher learning in the State to join hands for organizing this mega scientific event in the most befitting manner, particularly as it was being
held for the first time in Jammu and Kashmir.
He observed that this Science Congress shall provide a historical opportunity for the students and scientists to demonstrate their talent and scientific temper.
Observing that there is unlimited talent in the State, the Governor emphasized the need for identifying individual scientists in the various Universities and other science and technology institutions in J&K for presenting their papers and participating in the working sessions
of the Science Congress. Recalling the various INSPIRE programmes organised by different Universities in the State in the past four years, he added that the talented students and young scientists need to be encouraged to present their knowledge before
the galaxy of scientists at
the Congress.
Referring to the high importance of encouraging innovation in science, he stressed that the youth from the State who have made a mark in this arena must be identified and encouraged to exhibit their innovations at the Science Congress.
The Governor also
particularly urged the Vice Chancellors of the two State Farm Universities to identify themes which are J&K specific so that these could be included for deliberations in the working sessions of the Science Congress. He observed that climate change and global warming could be among the areas of focus of the Science Congress.
Prof R C Sobti, Vice Chancellor, Baba Saheb Ambedkar University, Lucknow and the President, Indian Science Congress Association, said that more than ten thousand scientists, including a large number of top scientists from within and outside the country, are likely to participate at the 5-day 101st Science Congress. He said that the main activities of this event will comprise Inaugural Ceremony,
14 Parallel Sessions on
identified themes, Science Communicators Meet, Women Science Congress, Children Science Congress, Science Exhibition, Book Exhibition and Valedictory Function. He thanked the Governor for taking
keen interest in organizing the upcoming Indian
Science Congress.
The meeting discussed issues relating to financing the varied expenditures, arrangements to be positioned for the Science Congress which included, interalia, accommodating the VVIPs and all others who are likely to participate in the Inaugural, Working and Valedictory sessions, preparation of mementos, presentation of awards, publication of a Souvenir, cultural and other logistics. The participants put forth several suggestions for successfully organizing this event.
Prof Sobti stated that, as suggested by the Governor, the Science Association had agreed that the Regional Science Congress, preparatory to the Indian Science Congress, should be held at Srinagar. In this context, the meeting held preliminary discussions for the Regional Science Congress being hosted by the Kashmir University in the last week of September 2013, which will involve
participation of over
100 scientists.
Among those who participated in the meeting included Prof Talat Ahmad, Vice Chancellor, Kashmir University; Dr M P S. Ishar, Vice Chancellor, Jammu University; Prof. Sudhir K. Jain, Vice Chancellor, Shri Mata Vaishno Devi University; Dr Tej Partap, Vice-Chancellor, SKUAST-Kashmir; Dr A R Trag, Vice Chancellor, Islamic University of Science and Technology, Awantipore; Prof I A Hamal, Vice Chancellor, Baba Ghulam Shah Badshah University, Rajouri; Dr Sameru Sharma, Principal, Government College of Engineering and Technology, Jammu;
Dr Ram A. Vishwakarma, Director, Indian Institute of Integrative Medicine, Jammu; Prof Showkat Ali Zargar, Director, SKIMS, Srinagar; Prof Rafiq Ahmad Pampori, Principal, Government Medical College, Srinagar; Dr Shashi Gupta, Principal, Government Medical College, Jammu;
Dr Nazeer Ahmad, Director, Central Institute of Temperate Horticulture, Srinagar; Navin K. Choudhary, Principal Secretary to the Governor; Prof. Naresh Padha and
Prof Meena Sharma of the Jammu University, who are the Local Secretaries for the Science Congress.
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The synchronization of an existing video to a new soundtrack is carried out through the phonetic analysis of the original soundtrack and the new soundtrack. Individual speech sounds, such as phones, are identified in the soundtrack for the original video recording, and the images corresponding thereto are stored. The new soundtrack is similarly analyzed to identify individual speech sounds, which are used to select the stored images and create a new video sequence. The sequence of images are then smoothly fitted to one another, to provide a video stream that is synchronized to the new soundtrack. This approach permits a given video sequence to be synchronized to any arbitrary utterance. Furthermore, the matching of the video images to the new speech sounds can be carried out in a highly automated manner, thereby reducing required manual effort.
1. A method for modifying a video recording having an accompanying audio track to produce a new video presentation with a different audio track, comprising the steps of:
analyzing said accompanying audio track by means of automatic speech recognition techniques to identify video frames in the video recording that are associated with individual speech characteristics in said accompanying audio track, and storing video image information from each of said frames in a database;
analyzing video image information from said frames to identify predetermined features associated with the video image, and annotating the video image information stored in said database with data relating to said features;
analyzing a sound utterance to identify individual speech characteristics in said sound utterance;
selecting video image information stored in said database according to the identified speech characteristics in said sound utterance, and assembling the selected items of image information to form a sequence; and
smoothly fitting the selected items of information in said sequence to one another in accordance with the annotated data to produce a video presentation that is synchronized to said sound utterance.
2. The method of claim 1 wherein said individual speech characteristics in said audio track and in said sound utterance include phones.
3. The method of claim 2 wherein said individual speech characteristics comprise diphones.
4. The method of claim 2 wherein said individual speech characteristics comprise triphones.
5. The method of claim 1 wherein said annotated data comprises control points in the video images, and said step of smoothly fitting the items of information in said sequence comprises the process of morphing between pairs of adjacent items of information in the sequence, using said control points.
6. The method of claim 5 wherein said control points identify the location of a speaker's lips in the video images.
7. The method of claim 1 wherein each item of video image information stored in said database is a subimage comprising a portion of an entire image in a video frame.
8. The method of claim 7 further including the step of incorporating the subimages into full video frames to produce said video presentation.
9. The method of claim 1 wherein the video recording includes an image of a person's head, and wherein each item of video image information stored in said database comprises a subimage of an area encompassing the mouth of the person in the image.
10. The method of claim 9 further including the step of incorporating the subimages of a person's mouth into a video frame that includes an image of a person's head.
11. The method of claim 1 wherein the step of analyzing the video recording comprises the step of analyzing said predetermined features to identify individual speech characteristics associated with said features.
12. The method of claim 11 wherein said predetermined features comprise control points which define the shape of a speaker's lips.
13. The method of claim 12 wherein said analysis comprises detection of the relative motion of said control points.
14. The method of claim 12 wherein said analysis comprises detection of the spatial distribution of said control points.
15. A method for synchronizing a video sequence having an accompanying audio track with a different audio track, comprising the steps of:
analyzing the audio track accompanying said video sequence by means of automatic speech recognition techniques to identify individual speech characteristics in said accompanying audio track;
analyzing a sound utterance in said different audio track by means of automatic speech recognition techniques to identify individual speech characteristics in said sound utterance; and
temporally modifying said video sequence so that identified individual speech characteristics in said video sequence are temporally aligned with corresponding individual speech characteristics in said sound utterance.
16. The method of claim 15 wherein said modifying step comprises the process of reordering frames of said video sequence to align them with individual speech characteristics in said sound utterance.
17. The method of claim 15 wherein said modifying step comprises the process of altering the timing of frames of said video sequence to align them with individual speech characteristics in said sound utterance.
18. The method of claim 15 wherein said individual speech characteristics in said audio track and in said sound utterance include phones.
19. The method of claim 15 wherein said sound utterance is similar to said audio track, and said modifying step includes the step of temporally warping said video sequence to align corresponding individual speech characteristics.
20. The method of claim 19 wherein said video sequence is temporally warped by removing one or more video frames from said sequence, and wherein the frames to be removed are selected in accordance with individual speech characteristics associated with the respective frames of the sequence.
21. The method of claim 15 wherein said modifying step comprises the steps of:
storing video image data for individual speech components that are identified in said soundtrack; and
retrieving stored video image data in a sequence corresponding to the identified individual speech components in said utterance, to produce a new video presentation.
22. The method of claim 21 further including the step of smoothly fitting the retrieved video image data in said sequence corresponding to successive individual speech components in said utterance.
23. The method of claim 22 wherein said smooth fitting step comprises the process of morphing between successive sets of retrieved video image data.
24. The method of claim 22 further including the steps of analyzing images in said video sequence to define control information therein, storing said control information with the stored video image data, and smoothly fitting the video image data in accordance with the stored control information.
25. The method of claim 24 wherein said control information comprises points in the video images which relate to features in the images.
26. A system for modifying a recorded video image stream to synchronize it to a soundtrack which is generated separately from the recorded video image stream, comprising:
means for automatically analyzing the recorded video image stream to identify sequences of images that are associated with individual speech characteristics;
a memory storing a database containing said identified sequences of images;
means for automatically analyzing said soundtrack to identify individual speech characteristics contained therein; and
means for selecting sequences of images contained in said database that correspond to individual speech characteristics that are identified in said soundtrack and assembling the selected sequences of images into a video image stream that is synchronized with said soundtrack.
27. The system of claim 26 wherein each of said automatic analyzing means comprises a speech recognition system.
28. The system of claim 27 wherein said speech recognition system is a Hidden Markov Model system.
29. The system of claim 27 wherein said speech recognition system is a neural network.
30. The system of claim 27 wherein said speech recognition system comprises a Hidden Markov Model system and a neural network.
31. The system of claim 26 wherein said individual speech characteristics include speech phones.
32. The system of claim 26 further including means for smoothly fitting said selected images to one another to produce said synchronized video image stream.
33. The system of claim 32 wherein said fitting means includes an image morphing system.
34. The system of claim 26 wherein said means for automatically analyzing the recorded video image stream includes means for defining control points in said images which relate to predetermined features, and means for analyzing said control points to recognize speech characteristics associated with said features.
35. A system for modifying a recorded video image stream to synchronize it to a soundtrack which is generated separately from the recorded video image stream, comprising:
means for analyzing the recorded video image stream to identify images that are associated with individual speech characteristics;
a memory storing a first database containing sub images, each of which comprises a predetermined portion of one of said identified images;
means for analyzing said identified images to define control features within the subimage portions of said images;
means for annotating said stored subimages with data relating to said defined control features;
a memory storing a second database containing full-frame images from said video image sequence, together with said defined control features;
means for analyzing said soundtrack to identify individual speech characteristics contained therein;
means for selecting subimages contained in said first database that correspond to individual speech characteristics that are identified in said sound track; and
means for incorporating the selected subimages into full-frame images stored in said second database, in accordance with the defined control features, to form a video stream that is synchronized with said soundtrack.
36. The system of claim 35 wherein said incorporating means aligns the control features in said subimages with corresponding control features in the full frame images, and cross-fades the subimages into the full-frame images.
37. The system of claim 35 wherein said incorporating means comprises a morphing system which morphs the subimages into the full-frame images in accordance with said control features.
38. A method for synchronizing a video sequence having an accompanying audio track with a different audio track, comprising the steps of:
analyzing the audio track accompanying said video sequence to identify individual speech characteristics in said audio track;
analyzing a sound utterance in said different audio track by means of automatic speech recognition techniques to identify individual speech characteristics in said sound utterance; and
reordering frames of said video sequence so that identified individual speech characteristics in said video sequence are temporally aligned with corresponding individual speech characteristics in said sound utterance.
39. A method for modifying a video recording that is associated with a first audio track to produce a video presentation corresponding to a second audio track, comprising the steps of:
analyzing said video recording to identify sequences of video frames that are associated with individual features in said first audio track, and storing said sequences of frames in a database in accordance with said identified features;
analyzing said second audio track to identify individual features therein;
selecting sequences of frames stored in said database according to the identified features in said second audio track, and assembling the selected sequences of frames to form a video stream that is synchronized to said second audio track.
The present invention is directed to the synchronization of video image sequences with speech soundtracks, and more particularly to a system that provides a realistic video presentation of a natural human uttering any arbitrary sentence or other sequence of sounds.
There are various situations in which it is desirable to have a video recording of a speaking person accurately track words which are different from those which were uttered during the original recording of the video image. One such application is the field of audio dubbing, in which the originally recorded soundtrack is replaced with a different soundtrack. In a simple case, after recording an image of an actor speaking a statement, it may be desirable to re-record the statement, for example to change emphasis or provide a different accent. Rather than recording the entire video sequence again, the redubbing process permits the actor to repeat the statement, with the desired modifications, and substitute the repeated statement for the originally recorded one.
In a more sophisticated video production, it may be desirable to utilize stock footage of an actor and replace the actor's spoken words with an entirely different speech soundtrack, perhaps in a different voice. For example, the original statement might be presented in a different language, or various special effects can be created, such as a child giving a speech in the original voice of a famous statesman.
In these types of applications, the original recorded image must be modified so that the speaker's lip movements are synchronized to the new soundtrack. In the past, the methods for achieving such synchronization have required extensive manual input and/or specialized processing that limited their applicability. One example of a prior art approach, which is based on image alignment, is described in U.S. Pat. No. 4,827,532. That patent is particularly directed to the replacement of a soundtrack in one language with a new soundtrack in a second language, which requires different lip movements for the speaker. In the technique disclosed in the '532 patent, a video recording is made of a new actor speaking the statements in the new language. Special markers are required to define the outlines of the actor's lips in the newly recorded image of the actor speaking in the new language, and the original video must be manually marked. Once the corresponding portions of the old and new video images have been identified, pixels of the original movie frame are modified to make them look like the original actor spoke the words of the new soundtrack.
The procedure disclosed in the '532 patent involves two types of video modification. First, the video sequence is temporally warped, in an effort to align the frames of the original image with the new sounds, so that the lip shapes match one another. Thereafter, visual warping, e.g., morphing, of the image is carried out to transition between non-continuous portions of the video that may result from skipping frames.
Both of these warping steps require a significant amount of manual input. As a result, lengthy video sequences with language dubbing are not easily produced. Furthermore, it is not possible in all cases to temporally warp a video sequence in such a way that the new lip shapes match the original shapes. For example, the image for a closed-lip sound cannot be warped into one for an open-lipped sound, because the teeth and/or tongue would be missing. A similar problem occurs for sounds which are produced with different lip protrusions. Thus, the types of changes which can be effected are limited. In addition, the new soundtrack requires a second video recording, so that the two recorded sequences can be visually aligned. As such, the procedure cannot be used with any arbitrary utterance as the new soundtrack. Rather, only soundtracks which have accompanying video images can be employed.
Other approaches have been used in the field of animation, so that a character's mouth accurately tracks spoken words. However, the images that are used in these approaches are synthetic, and their associated synchronization techniques are not suited for use with video images of a natural person's face.
Accordingly, it is desirable to provide a technique which permits any given sound utterance to be substituted for the soundtrack of a previously recorded video sequence, without requiring a video recording of the new sounds being uttered. It is further desirable to provide such a method which readily lends itself to automation, to thereby minimize the amount of manual input that is required.
In accordance with the present invention, these objectives are achieved through the modification of frames of an existing video recording to create a new video stream which matches any arbitrary utterance, using a combination of speech recognition techniques and image processing. One embodiment of the synchronization process involves three major steps. First, a video recording is analyzed and all possible lip movements are defined and stored in a database. In practice, it may be necessary to store only a limited number of different visual image sequences in the database, to approximate the visual aspect of all spoken sounds. The visual image sequences are analyzed to identify salient features, and the information stored in the database is annotated with these features. As a second step, a new soundtrack is phonetically transcribed, and an image sequence for each transcribed sound is retrieved from the database. As a final step, the retrieved image sequences are fitted smoothly together using the annotated information, to present a modified video stream that is synchronized to the new soundtrack.
In a related application of this procedure, the new soundtrack comprises the same sentences as those spoken in the original video recording. However, the new sentences may provide a different emphasis, accent, voice, gender or age. The video images are temporally matched to the new audio track through appropriate time warping, to synchronize the video to the new audio message.
In general, therefore, the present invention involves the analysis of a video recording to associate recorded sounds with corresponding images, and the subsequent matching of images from the original video recording to the phonetic components of the new sound. This technique permits a given video recording to be synchronized to any arbitrary audio track, without requiring a separate video recording of the new soundtrack or generation of any artificial speech or graphics. The matching of the video sequence to the new sounds is carried out in a highly automated manner, thereby reducing the amount of manual effort that is required for audio dubbing and the like.
Further features of the invention, and the advantages attained thereby, are explained in detail hereinafter with reference to specific examples illustrated in the accompanying drawings.
FIG. 1 is a flow diagram of the overall process of the present invention;
FIG. 2 is a more detailed flow diagram of the procedure for creating an annotated database of sound-related image sequences;
FIG. 3 is a schematic functional illustration of the process for creating a viseme database from a video recording;
FIG. 4A is a schematic functional illustration of a first embodiment of the process for creating a new video stream that is synchronized to a new audio track;
FIG. 4B is a more detailed flow diagram of the procedure for assembling a new video string from the database and a new soundtrack in accordance with the first embodiment of FIG. 4A;
FIG. 5A is a schematic functional illustration of a second embodiment for creating a new video stream;
FIG. 5B is a flow diagram of the process carried out in the second embodiment of FIG. 5A;
FIG. 6 is an example of a video frame in which control points on a speaker's lips have been marked;
FIG. 7 is an example of the video frame in which a new lip image has been incorporated;
FIG. 8 is a schematic functional illustration of an alternate procedure for synchronizing a video sequence to a new soundtrack; and
FIG. 9 is a flow diagram of the alternate procedure shown in FIG. 8.
To facilitate an understanding of the present invention, it is described hereinafter with reference to specific examples in which the soundtrack for a video recording of a person uttering a sound is replaced with a different soundtrack. The examples are related to the replacement of one set of spoken words, e.g. a sentence, with another set of spoken words. However, the practical applications of the invention are not limited to words. Rather, its principles can be applied to other sounds as well, for example singing and non-speech utterances such as laughs, coughs, etc. Therefore, in the context of the present invention, the term "utterance" is employed in a generic sense to refer to spoken words, notes that are sung, and any other sounds which are orally produced and capable of classification using speech-related descriptions.
In setting forth the following examples of the invention, certain specific techniques are identified for various types of video and audio analysis. It will be appreciated, however, that these techniques are exemplary, and that the invention can be practiced using other techniques which provide similar results. Furthermore, it will be understood that the principles of the invention are not limited to the specific illustrative implementations described herein. Rather, there are a number of practical applications of the invention, as discussed in greater detail at the conclusion of the specification.
An overview of the procedure which is employed in one embodiment of the present invention to synchronize a stock video recording to a new soundtrack is illustrated in the flow diagram of FIG. 1. Referring thereto, a video recording of a natural person who is speaking or singing is analyzed at Step S1, to associate characteristic sounds in the utterance with specific video image sequences. An image sequence that is identified as being associated with a given sound is analyzed at Step S2 to locate salient features therein. For example, control points which identify the position of the speaker's lips can be established within each frame of the sequence. The analyzed video image sequences are stored in a database at Step S3, which is indexed according to the characteristic sounds associated with each image sequence. The stored image sequences are annotated with the control points or other salient features determined in the image analysis step. Thereafter, at Step S4, a new sound utterance, such as the voice of a different speaker, is analyzed to identify the characteristic sounds therein. At Step S5, identified sounds in the new soundtrack are matched with the corresponding images of the original recording. In one embodiment of the invention, an appropriate image sequence is retrieved from the database for each identified sound in the new soundtrack, and all of the retrieved image sequences are strung together at Step S6A. The sequence of images is then smoothed at Step S7A, for example by means of a morphing process which utilizes the established control points, to produce a video stream of the person speaking the new utterance. In an alternate embodiment of the invention in which the new soundtrack is close to that of the original recording, e.g. the same sentence is spoken, at Step S6B the matching is achieved by temporally warping the original video or the new audio, as appropriate, to align the characteristic sounds of the original recording with those of the new soundtrack.
The creation of a database of sound-indexed and annotated images at Steps S1-S3 of FIG. 1 is illustrated in greater detail in the flow diagram of FIG. 2. Basically, a video recording, with its accompanying audio track, first undergoes a speech recognition procedure. The purpose of this procedure is to identify recognizable components, or features, which make up the recorded utterance. In one embodiment, these components comprise the individual phones of speech, i.e. a set of the smallest units of speech. More preferably, individual diphones or triphones of speech are utilized, since they include sufficient context and better model acoustic and visual transitions. As used in the context of the present invention, the term "phone" is intended to refer to diphones and triphones, as well as individual phones of speech. Different words or different pronunciations of the same word can be generated by stringing together these phonetic units, with the use of conventional pronunciation dictionaries. A variety of acoustic features, such as MFCC, RASTA-PLP and LPC can be used to classify the different units of speech.
Various types of speech recognition devices are well known in the art, and can be employed to identify the component sounds of the recorded speech. For example, a neural network can be trained to operate as an automatic speech recognition device. In a preferred embodiment of the invention, a Hidden Markov Model (HMM) system is employed as a phonetic speech recognizer. A description of the use of an HMM system for such a purpose is described in Rabiner, Laurence R., "A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition", Proceedings of the IEEE, Vol. 77, No. 2, pp. 257-286, February 1989, the disclosure of which is incorporated herein by reference.
Referring to FIG. 2, at Step S10 the speech recognizer is first trained to recognize the sound components which are to be employed for classification purposes. For example, an HMM system can be trained to recognize phones by means of a training device such as the Hidden Markov Toolkit from Entropic Research Lab. If the same person's voice is to be employed in both the original video sequence and the new audio track, the HMM system can be trained on only that person's voice. Alternatively, one speaker-dependent HMM system can be used for the original soundtrack, and a different speaker-dependent system can be employed to analyze the new sound utterance, if sufficient training data is available for each speaker. More preferably, however, the speech recognizer is trained to be speaker independent, so that any arbitrary spoken utterance can be substituted for any original soundtrack. This approach is particularly desirable for those situations in which the original soundtrack is short, and very little training data is available for the speaker.
To avoid adverse results from the respective characteristics of different microphones used in the original and new soundtracks, a channel-invariant acoustic feature extraction system is preferably employed to provide the input information to the HMM system. One example of such a system is the RASTA-PLP system described in Hermansky et al., "Compensation for the Effect of the Communication Channel in Auditory", Proc. Europ. Conf. on Speech Comm. and Tech., 1991, pp. 1367-1370, and in U.S. Pat. No. 5,450,522, the disclosures of which are incorporated herein by reference. Other approaches to channel invariance can also be employed.
After the speech recognizer has been trained to identify individual phones in a spoken utterance, it is used to analyze the particular soundtrack that accompanies the video recording of interest and construct a database of relevant image sequences. The procedure for generating the database of image sequences is schematically depicted in FIG. 3. Referring thereto, a stock video recording 10 comprises a series of image frames 12 and an accompanying audio track 14. The stock video is played back, and the recorded sounds are analyzed in a speech recognizer 16, which identifies individual phones in the recorded speech (Step S11 in FIG. 2). For each phone which is recognized in the recorded soundtrack, video image data corresponding to the identified sound is recorded in a database 18 (Step S12). The stored video image data could comprise a single image, e.g. one video frame, for each phone. For better results, a sequence of images is stored, e.g. 1-11 frames, depending on the duration of the phone, to encompass the full pronunciation of the phone. The recorded image data is indexed in the database 18 in accordance with the particular phone with which it is associated (Step S13).
Each frame or sequence of frames stored in the database also undergoes image analysis at Step S14, to locate salient information in the stock video that can be subsequently used to construct a new video presentation. For example, as described in greater detail hereinafter, the image can be analyzed to locate control points, which identify the location and orientation of the speaker's lips within each frame. Once these features have been identified, they are stored in the database along with the images, at Step S15. The completed database 18 contains a video image sequence of the speaker's lip position that corresponds to each spoken sound that was recorded, annotated with the relevant control points or other feature information.
According to one established standard for speech recognition, known as the TIMIT phone set, there are sixty-one different phone categories which characterize human speech. Basically, each phone represents a different sound that can be uttered by a person. However, different phones may have the same visual appearance to a viewer. For example, a speaker's lips are in the same position to pronounce the sounds for each of the letters "b" and "p". Similarly, the pronunciation of the sounds associated with the consonants "d" and "t" present the same visual impression. In the context of the present invention, the visual appearance of a spoken phone is identified as a "viseme." The sixty-one categories of auditory phones can be mapped to a set of ten visemes. Thus, a compact version of the database need only contain ten entries, respectively associated with the ten visemes. If sounds other than spoken words are also of interest, the TIMIT phone set can be extended to add categories for non-speech utterance, such as coughs, laughs, burps, clicks and the like. In such a case, the set of visemes stored in the database 18 is similarly extended to encompass these additional non-speech categories.
Once the database 18 has been constructed, it can be used to assemble a video stream that is synchronized to a new utterance. A simple version of this process is conceptually depicted in the schematic illustration of FIG. 4A and the flow diagram of FIG. 4B. Referring thereto, a new soundtrack is provided to the speech recognizer 16. In the illustrated example, the soundtrack is recorded on a suitable medium, such as a magnetic tape 20. In practice, however, the new soundtrack need not be pre-recorded. For example, words uttered by a speaker can be directly fed into the speech recognizer 16 via a microphone, as they are being spoken. The speech recognizer identifies each of the individual sounds in the new utterance, e.g., the successive phones, at Step S20. Each identified sound provides an index that is used to access the database 18 at Step S21. For each such sound, the corresponding video image sequence, e.g., viseme, is selected from the database at Step S22, and the retrieved visemes are assembled into a string 22 of concatenated viseme sequences at Step S23. In the example of FIG. 4A, four selected viseme sequences 22 respectively correspond to four successive phones in the new soundtrack on the magnetic tape 20.
Since adjacent image sequences in the assembled string 22 may relate to non-successive portions of the original video recording, there might be abrupt changes from one image sequence to the next. Accordingly, it is desirable to smoothly fit the sequential images to one another. For this purpose, the sequences of images retrieved from the database 18 are preferably processed in an image morphing device 24 (Step S24). This device essentially functions to morph one image into the next successive image in a conventional manner, using the control features that are stored with the images in the database. As a result, the images smoothly transition from one to another, to more closely resemble the natural movement of the speaker. The smoothly fitted images are then combined with the new soundtrack 20 at Step S25, to produce a new video stream 26 in which the image of the speaker is synchronized with the sounds in the new soundtrack.
In the embodiment of FIG. 4A, the video data that is stored in the database 18 can comprise complete video frames from the original stock recording 10, each of which might include the full head of the speaker. If the spoken material is of any appreciable length, it is quite possible that the speaker's head will move during the recorded session. For non-portrait images, which encompass a larger portion of the speaker's body, the possibility of movement is even greater. Because of these movements in the original recording, when the various frames are reassembled to create the new sequence 22, jerky movements of the speaker's head or body may result. Similarly, if the speaker presents exaggerated expressions, e.g., raised eyebrows, unnatural movements may appear in the reconstructed sequence 22. To limit the possibility of such, rather than storing and using complete video frames to generate the new sequence 22, it is sometimes preferable to employ subimages which contain only those portions of a video frame that are necessary to achieve synchronization with the new utterance. The subimage therefore might comprise the lips of the speaker, and perhaps a small area surrounding the mouth. Since the jaw of a person typically moves in concert with the lower lip during speech, it is preferable to include the jaw in the subimage as well.
An embodiment of the invention which employs subimages is depicted in FIGS. 5A and 5B. In this implementation, the final synchronized video stream 26 is generated by "pasting" or blending each retrieved sequence of subimages into a full image of the speaker's head. In one embodiment, the successive subimages can be pasted onto a still-frame image of the speaker. For a more naturally appearing presentation, the subimages are incorporated into a running presentation of the speaker. For this purpose, the database 18 is composed of two parts 18a and 18b. Subimages which correspond to the individual visemes are stored in one portion 18a of the database. Each stored subimage is indexed according to its associated viseme, and annotated with relevant features determined through image analysis, as in the previous embodiment. The second portion 18b of the database contains full-frame images 12 of the original stock video 10. In operation, subimages retrieved from the database 18a are pasted into full-frame images retrieved from the database 18b to produce the final video sequence.
To ensure the correct placement of the subimages within the video frames, the frames stored in the database 18b are annotated with control points that correspond with those in the stored subimages. For example, a single control point might be located at the center of the top edge of the speaker's upper lip. This control point is identified in the original recording stored in the database 18b, and in each of the subimages stored in the database 18a. In operation, subimages are retrieved from the database 18a to form a concatenated viseme sequence 22, as in the embodiment of FIG. 4A. The subimages are then morphed to one another, at Step 24a, to provide a smoothed presentation. One example of a morphing technique that is suitable for this purpose is described in "Feature-based Image Metamorphosis" by T. Beier and S. Neely, Computer Graphics 26, 2 (1992), pp.35-42, the disclosure of which is incorporated herein by reference. The smoothed sequence of subimages is pasted into a series of successive full-frame images retrieved from the database 18b, at Step 26a. When a subimage is pasted into the original full-frame sequence, the control point of each frame in the subimage sequence is aligned with that of a corresponding frame of the original recording, to ensure that the subimage of the mouth is located at the proper position within the video frame.
Preferably, a plurality of control points are employed to align the speaker's lips in the subimage and the full frame image. To this end, an automatic visual tracking algorithm is utilized to identify the lip boundaries of the speaker. Conventional contour tracking algorithms can be used to define the outer boundary of the speaker's lips. An example of a suitable contour tracking algorithm is described in Kaas et al., "SNAKES: Active Contour Models", Proc. of the First Int. Conf. on Computer Vision, London 1987. If the resolution of the video image is low, a grey level based algorithm can be employed, such as the eigen-images approach described in Pentland et al, "View-Based and Modular Eigenspaces for Face Recognition", Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 1994, pps. 84-91. Most preferably, the tracking algorithm is one which identifies control points on both the outer and inner boundaries of the speaker's lips. An example of such an algorithm is described in co-pending application Ser. No. 08/651,108. An example of a video image of a speaker, in which the inner and outer lip control points have been automatically identified, is illustrated in FIG. 6. These control points are stored with each subimage recorded in the database 18a, and each full-frame image in the database 18b.
The concatenated and smoothed sequences 22 of the subimages are pasted into the final video stream 26 by means of the pasting process of Step S26a, which utilizes the recorded control points. At a coarse level, the control points are first used to determine the location of the new lip subimages in the video frame, and whether any rotation and scaling needs to be applied to them. After the general location, scaling and orientation of the images are determined, the control points are used to align the subimage with the full-frame image, and fade the new lip images into the frame. This procedure can be carried out using any suitable conventional morphing program. One example of a morphing program that can be used in this context is the public domain software "Morphine". An example of a video frame corresponding to the original image of FIG. 6, but with a new morphed lip subimage, is illustrated in FIG. 7.
The duration of a phone is relatively short, and may encompass only three or four successive frames in the video sequence. In such a case, to achieve a smooth fit of images it may not be necessary to use a morphing process, which comprises both cross-fading and warping of the images. Rather, it may be sufficient to simply cross-fade the images over the course of a few frames, to obtain an acceptable blending of the subimage into the original video recording. For example, after the subimage is suitably scaled and rotated, it is cross-faded into the original recording in such a manner that the position of the speaker's upper lip remains the same in both the original and new images. Further in this regard, it is not necessary to blend the subimages together, prior to pasting them into the full-frame images. Rather, the blending can be inherently implemented as part of the pasting process. In other words, Steps S24a and S26a of FIG. 5B can be carried out in a single procedure.
There are several different approaches that can be used to assemble the database 18 and subsequently retrieve the stored image information to construct the image sequences 22. In the relatively simple embodiment described above, a minimum number of visemes, approximately ten, can be stored in the database. In this embodiment, each identified phone in the new soundtrack is used to select a corresponding viseme from the database, to form the string of image sequences 22. This particular implementation is particularly useful in those situations where a limited amount of data is available, for example where the analyzed portion of the original stock video is relatively short.
In a more complex embodiment, the information stored in the database 18 can comprise bi-visemes. A bi-viseme is the visual image that corresponds to the transition from one phone to the following phone. The bi-visemes are indexed in the database 18 by means of diphones, i.e., temporal phone pairs. In this embodiment, the images are retrieved from the database 18 on the basis of diphones identified in the new soundtrack. For example, the spoken word "bar" consists of a series phones corresponding to the sounds for "b", "ah", and "r", accompanied by silence at the beginning and the end of the word. When this spoken word is analyzed, the speech recognizer 16 produces an output signal for the diphone "sil-b", i.e. silence followed by the sound for the consonant "b". The bi-viseme for this diphone is selected from the database 18. The speech recognizer 16 then produces an output signal for the diphone "b-ah", and the corresponding bi-viseme is retrieved from the database to form the next image sequence in the string 22. The next diphone corresponds to the sound "ah-r", and its corresponding bi-viseme is retrieved from the database, to form the next image sequence in the string 22. Finally, the bi-viseme for the diphone "r-sil", i.e. silence at the end of the word, is selected from the database. If a bi-viseme for a particular diphone is not stored in the database, the corresponding single viseme is selected. Thus, in the foregoing example, if there is no stored bi-viseme for the sound "ah-r", the single viseme for the phone "r" is selected.
In a more sophisticated implementation of this embodiment, several alternative bi-visemes can be selected with the use of dynamic programming techniques. In this implementation, an energy function can be defined which consists of three terms. One term measures the quality of the visual match between successive bi-visemes in the new utterance. This matching might be carried out, for example, by comparing the grayscale values of corresponding pixels in the successive bi-visemes. The second term in the energy function measures the difference between the length of the bi-viseme stored in the database and the corresponding diphone in the new utterance. The third term in the energy function is a penalty value that is assigned in those situations where a single viseme is used instead of a bi-viseme. The energy function is computed for each of the alternative combinations of bi-visemes, and the one which exhibits the minimum energy function is selected for use in the image sequence 22.
In the preceding embodiments of the invention, audio analysis is employed to recognize the phones in the original soundtrack, to identify and store corresponding viseme image sequences. In some cases, the original recording may not readily lend itself to this type of analysis. For example, other sounds may overlay the voice of the speaker of interest, such as when two people speak simultaneously or background music is sufficiently loud to corrupt the input to the speech recognition system. In another example, the time alignment between video and audio tracks may drift, as sometimes happens in digital systems, so that the viseme image sequence at a certain point does not accurately correspond to the detected phone at that point.
In an alternate embodiment of the invention, image analysis is employed to identify the individual visemes, rather than audio analysis. In this embodiment, the control points in each frame, or more preferably a sequence of frames, are provided to any suitable pattern recognition or gesture recognition system, such as a Hidden Markov Model system or a neural network. The system is trained to recognize the spatial distribution and/or relative movement of the lip control points that are associated with different respective visemes, and is not affected by multiple sounds in the original soundtrack or misalignment between the video and audio tracks. In operation, the recognition system generates viseme labels for input image sequences, which are used to store and index those image sequences in the database 18a. Thereafter, the system operates in the same manner as the previously described embodiments.
In the foregoing examples of the invention, a database is constructed of image sequences corresponding to identified sounds, and a new video stream is assembled from the recorded images in accordance with the new soundtrack. If, however, the new soundtrack is substantially similar to the originally recorded sounds, the reconstruction of the video stream may not be necessary. For example, in the production of television advertisements, it is sometimes desirable to have an actor re-record a statement, to delete an unnecessary pause or provide different emphasis. In such a case, the words in the new soundtrack are the same as those of the original recording, but the timing may be different. In this type of situation, the present invention can be employed to modify the originally recorded video, to synchronize it with the re-recorded soundtrack, utilizing time warping techniques.
This embodiment of the invention is depicted in the schematic illustration of FIG. 8 and the flow diagram of FIG. 9. Referring thereto, the original recording 10 is analyzed at Step S31 to identify individual phones, or other characteristic components of speech. The particular frames which correspond to the different components are recorded in a database 19 at Step S32. A new sound recording 20 undergoes similar speech analysis at Step S33. It may consist of the same speech components, e.g. phones for the word "bar", but the timing between the individual sounds may be different from the original recording. Once the corresponding speech components have been identified in both the original recording and the new soundtrack, the recording undergoes a time warping process at Step S34, to synchronize it to the new soundtrack. In the example of FIG. 8, a frame is dropped from the original recording, so that the remaining frames in a new video sequence 27 correspond to the timing of the new speech soundtrack 20.
In a situation where one or more frames must be dropped from the video recording, a decision must be made as to which frame(s) to drop. In the context of the present invention, a set of selection rules which are based on the phones associated with the respective frames can aid in this process. Typically, the lip movements associated with consonant sounds are much quicker than those for vowel sounds. For example, the closure of the lips to pronounce the sound for the letter "b" might occur over the course of one or two video frames, whereas the following vowel sound might extend over several frames. In such a case, the predefined set of rules might specify that a frame associated with the closure of the lips and start of the release of the "b" sound is to be selected, and one or more subsequent frames associated with a vowel sound can be dropped. Such an approach maintains the appearance of correct lip motions for the compressed time audio track.
As an alternative to modifying the original video recording, the new speech soundtrack can be time warped, to temporally align it with the original video. Whether the original recorded video or the new soundtrack is temporally warped to align it to the other can be a matter of choice. Generally speaking, however, it is desirable to warp the one which is the slower of the two, to synchronize it with the faster recording. Any suitable time-scale modification technique, such as synchronous overlap-and-add (SOLA), can be employed to temporally warp the audio or video track.
Once the time warping process is complete, the video sequence is combined with the new soundtrack 20 at Step S35, to form a new audio-visual presentation 28. This embodiment of the invention is particularly desirable for those cases in which the words in the two soundtracks are the same as, or substantially the same as, one another, since it does not require lip tracking, control-point designation or viseme alignment. Examples of suitable applications for this embodiment include redubbing of movie soundtracks, and karaoke systems in which a person sings to an accompanying video presentation.
The foregoing aspects of the invention are preferably implemented in a computer system (not shown) which is suitably programmed to perform the functions of speech recognition and image morphing. Since these procedures are conventionally known in themselves, they have not been described in detail herein. The database can be stored in any suitable memory associated with the computer system, e.g. a magnetic hard disk. The original video recording and the new soundtrack can likewise be stored in the computer system. The output video stream that is synchronized to the new soundtrack can be initially stored in the computer's memory, and then transferred to some other medium suitable for playback, e.g. a video tape cassette, or played back directly from the computer.
It will be appreciated by those of ordinary skill in the art that the present invention can be embodied in other specific forms without departing from the spirit or essential characteristics thereof. Specifically, although the embodiments of the invention have been described with reference to their implementation in audio dubbing, the practical uses of the invention are not limited to these types of applications. As one example, the invention can also be employed to provide a low bandwidth video phone. In such a situation, the transmitter only needs to send the audio channel and a viseme sequence. The receiver can utilize the viseme stream, along with previously stored video data, such as full-frame images, to reconstruct a lip-synchronized image of the caller. As another example, the invention can be used to provide new types of user interfaces for computers, in which a well-recognized personality can speak to the computer user with instructions or requests for information. In another embodiment, the invention can be employed to create avatars in virtual reality games, or the like, wherein an image of any given face can speak with the player's voice.
It will be appreciated by those of ordinary skill in the art that the present invention can be embodied in other specific forms without departing from the spirit or essential characteristics thereof. For example, although neural networks and Hidden Markov Model systems have been individually described as suitable implementations for automatic speech recognition, some combination of the two types of systems could be employed for this purpose. The presently disclosed embodiments are therefore considered in all respects to be illustrative, and not restrictive. The scope of the invention is indicated by the appended claims, rather than the foregoing description, and all changes that come within the meaning and range of equivalents thereof are intended to be embraced therein.
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GANGS 101: Topics Covered: Indicators of gang involvement, who is a gang member, levels of gang involvement, current gang trends, differences between Denver gangs/hybrid crews, and differences between gang vs. tagging crew graffiti.
GANGS102 Denver GANGS EXPOSED: Overview of Denver gangs including territory, history, affiliation, rivals, symbols and more.
GANGS 103: Topics Covered: Interventions to utilize with gang involved individuals including ex-gang members that will give examples of what interventions worked for them.
ADULT FULL DAY TRAINING: 8 hours 50 or more people; Adults Adaptation of 101, 102 and 103 trainings. Includes questions and answer session.
Gang Rescue and Support Project is a program of METRO DENVER PARTNERS 2004-2015 © Metro Denver Partners. All Rights Reserved


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Google Blogoscoped tipped me off on this link. Seems Engadget has a page which gives some pretty good direction on how to create your own annotated multimedia Google map.
There is some pretty serious direction here which includes inserting pictures and movies from the annotations. I'd like to see an example of this.


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After calculating how much your small law practice needs to make a profit and your reasonable hourly rate, you are ready to consider the available pricing options. There are various ways to price your legal services. This article discusses fixed fee and retainer pricing.
Fixed Pricing
Under a Fixed Pricing, or "Flat Fee," a fixed amount paid is paid by the client up front prior to any substantial work being performed. This model is most commonly used in criminal and misdemeanor cases. Due to the intricate and time-intensive nature of handling criminal matters - multiple court appearances, lengthy pleadings and unforeseen motions - criminal cases are not well suited for contingency fees or hourly rates.
This model is also useful for form-intensive matters that do not require an excessive amount of your time, such as straightforward personal bankruptcy, uncontested divorce, and routine immigration matters. Very often, these kinds of cases are complicated by the client's circumstances, so prior to accepting a case for a flat fee, it is important to ask the right questions during client intake. These questions should help uncover any red flags that would make a flat fee a disadvantageous pricing arrangement.
Similar to fixed pricing, a retainer is money paid in advance by the client. Ideally, the retainer amount should reflect a certain number of your billable time at a given hourly rate. By accepting the retainer, you are agreeing to represent the client until the retainer amount has been exhausted.
Retainers are commonly used in recurring client-attorney relationships, where the requests for services is not strictly matter-driven and may encompass a multitude of legal tasks. For example, if the client is a small business, they may need you to write letters, apply for permits, perform business formation activities, and debt collection.
This pricing model has positive cash-flow advantages because the money is provided in advance of services. On the other hand, the client may expect you to perform services that exceed the retainer amount. Thus, prior to accepting a retainer, you and the client should discuss what will happen when the initial retainer has been exhausted. Will you charge on an hourly rate? Or will you require another retainer?


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Founding Dean of Regent University School of Law to SpeakOctober 23, 2006
Liberty University School of Law welcomes Herbert W. Titus, Founding Dean of Regent University School of Law, as the next speaker for the 2006-07 Speakers' Forum. The presentation will start at 2:15 P.M. on Friday, October 27, and will be held in the Student Services Center at the law school. Mr. Titus, who is currently Of Counsel to William J. Olson, P.C. in McLean, Virginia, will make his presentation titled, "The Bible: God's Lawbook for the Nations." The law school welcomes members of the university and legal community to Speakers' Forum events.
Mr. Titus taught constitutional law, common law, and other subjects for nearly thirty years at five different American Bar Association-approved law schools. From 1986 to 1993 he served as the founding Dean of Regent University School of Law in Virginia Beach, Virginia. Prior to his academic career, he served as a Trial Attorney and a Special United States Attorney with the United States Department of Justice in Washington, D.C. and Kansas City, Missouri. The general practice he is currently engaged in concentrates on constitutional strategy, litigation, and appeals.
He earned his Juris Doctorate (cum laude) from Harvard Law School and his Bachelor of Science degree in Political Science from the University of Oregon (Phi Beta Kappa). He is an active member of the bar of Virginia and an inactive member of the bar of Oregon. He is admitted to practice before the United States Supreme Court, the United States District Court for the Eastern District of Virginia, the United States Court of Claims, and the United States Courts of Appeals for the Sixth, Tenth, District of Columbia and Federal Circuits. He and his wife, Marilyn, have been married 39 years and reside in Chesapeake, Virginia. They have four children and twelve grandchildren.
In its third year, the Speakers' Forum is designed to introduce law students to accomplished leaders who serve in a variety of legal positions. For more information about Liberty University School of Law or about the Speakers' Forum, please write email@example.com or call 434-592-5300.


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TRENTON, N.J. -- Following intense scrutiny over the cost of its football stadium expansion and disclosures about the compensation package for football coach Greg Schiano, Rutgers University created a new financial oversight position for its athletic department.
The university on Thursday hired Richard J. Costello to the position of deputy director of athletics-finance and administration. He starts next month.
Costello, currently the athletic director at Delaware State University, comes to Rutgers as some faculty, students and alumni are questioning the university's investment in big-time college sports.
Phone and e-mail messages left for Costello on Thursday were not immediately returned.
Rutgers president Richard L. McCormick said in a news release that Costello "brings an impressive background in finance, budget planning and management of intercollegiate athletics to this very important position."
William C. Dowling, a professor of English who has been one of the chief critics of the athletics expansion, called Costello's appointment a "last desperate attempt in damage containment."
Costello will receive an annual salary of $195,000, receive a temporary housing allowance of up to $15,000 over eight months and get an annual automobile stipend of $12,000.
Dowling said McCormick is merely adding another layer of bureaucracy.
"The only logical outcome I can see to this is he will then appoint another director of oversight to watch this director of oversight and pay the next guy $400,000," Dowling said.
University spokesman Greg Trevor said Costello's salary is similar to what he was making at Delaware State.
Schiano, whose contract this year is worth $1.6 million, gets an additional $250,000 per year from Nelligan Sports Marketing, a firm the university hired in 2000 to market the athletic program. The payment is guaranteed by Rutgers if sponsorships don't cover it.
In July, McCormick ordered an internal review of financial controls in July as a series of reports in The Star-Ledger of Newark raised questions about athletic department expenditures.
The state comptroller's office has requested documents on the athletic department, including financial details of the $102 million expansion of Rutgers Stadium.


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Built sometime between 1828 and 1845, this one-room schoolhouse was better known as #16 in the Potsdam district. We have met several former students and a substitute teacher since opening as "Mom's" in 2003.This is a picture we have of their memories.
The desks faced the blackboards that were on the same wall as our trivia board. (That slate is from a school in Ogdensburg and Dick made the frame for it). The teacher's desk was to the right of the boards approximately where our groceries are and the wood stove where I prepare and cook your meals and desserts. Under the windows were the shelves holding encyclopedias and other books, with lunch boxes lining the top. Rest and nap time was in the corner where our music plays and the little window beside the music was the back door to the woodshed and outhouses. The children walked, rode bikes or occasionally a pony to school and in the wintertime some skied.
Mom's Journal
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