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a survey of methods for face detection
A Survey of Methods for Face Detection Andrew King 992 550 627 March 3, 2003 Contents 1 Introduction 1.1 1.2 The Problem of Face Detection . . . . . . . . . . . . . . . . . Current Work . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2 4 2 Mathematical Models and Approaches 7 3 Classifiers 18 4 Results and Conclusions 4.1 4.2 26 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Conclusions and Future Work . . . . . . . . . . . . . . . . . . 27 1 Chapter 1 Introduction 1.1 The Problem of Face Detection In this paper we focus specifically on the problem of face detection in still images. Obviously the most straightforward variety of this problem is the detection of a single face at a known scale and orientation. Even this, it turns out, is a nontrivial problem. The most immediate application that comes to mind for face detection is as the first step in an automated face recognizer [12]. Thought of in this sense, face detection can be applied to systems for things such as automated surveillance and human traffic census. In and of itself, however, face detection is a fascinating problem. Efficient 2 face detection at framerate is an impressive goal; it is an analogue to face tracking (on which the literature, due to the subject's obvious application to human-computer interaction [6], is extensive) that requires no knowledge of previous frames. As such, it is obviously a more challenging problem (particularly as many face tracking approaches are designed for human-computer interaction schemes designed specifically to this end). Furthermore, fast face detection has an apparent application to practical face tracking in the sense that it can be used to initialize tracking, e.g. when an interaction subject enters the frame or appears from an occluded position. Another reason that face detection is an important research problem is its role as a challenging case of a more general problem, i.e. object detection, for which the applications, once not restricted to faces, are manifold. Face detection is a beautiful paradigm for the general problem for several reasons. A face is naturally recognizable to a human being despite its many points of variation (e.g. skin tone, hairstyle, facial hair, glasses, etc.). Obviously a human being is able to detect a face in the context of an entire person, but we want a simple, context-free approach to detection. Another source of difficulty for faces is the complex 3-dimensional shape of one's face, and the resulting difference in the appearance of a given face under different lighting 3 conditions, even in an otherwise identical environment [12]. There may be object detection methods that work well for more easily identifiable objects such as blocks, but a method that works well for faces can generally be trusted with the task of detection for a wide range of complex object structures. The generality of detecting faces in a single greyscale image is a major challenge. We have no standard method for determining illumination data, scene structure, or context of sub-images without performing extensive operations on the image before even considering faces. Hence a successful strategy for face detection will be able to dodge environmental tricks and traps, but cannot ever be expected to perform perfectly. 1.2 Current Work There are various solutions to this problem, most of which deal with faces at arbitrary (at least, within a reasonable range) scales, though most assume an upright face (the method to be used for rotated faces is an obvious exhaustive analogue to any detection method for upright faces). Most of the methods discussed in this paper are concerned only with detecting forwardfacing faces. Of these methods, only Schneiderman and Kanade's statistical 4 method considers profile detection [11]. However, their method considers only three face orientations, and practically speaking, each orientation is treated as a different object. The effects of this approach for detecting faces at various orientations is discussed in Chapter 4. Schneiderman and Kanade apply statistical likelihood tests, using feature output histograms to create their detector scheme in [11]. Rowley and Kanade use neural network-based filters in [10], obtaining good early results in what has apparently become a benchmark of sorts for face detection schemes. In another early work, Papageorgiou et al. propose a general object detection scheme which uses a wavelet representation and statistical learning techniques [8]. Osuna et al. apply Vapnik's support vector machine technique to face detection in [7], and Romdhani et al. improve on that work by creating reduced training vector sets for their classifier in [9]. Fleuret and Geman attempt a coarse-to-fine approach to face detection, focusing on minimizing computation in their approach [3]. In perhaps the most impressive paper, Viola and Jones use the concept of an "integral image", along with a rectangular feature representation and a boosting algorithm as its learning method, to detect faces at 15 frames per second [13]. This represents an improvement in computation time of an order of magnitude over previous 5 implementations of face detection algorithms. In Chapter 2, we describe the various mathematical models used for these methods. In Chapter 3, we specifically discuss the classifier for each approach. In Chapter 4, the results of these approaches are analyzed and compared. 6 Chapter 2 Mathematical Models and Approaches Every method addressed in this paper uses a learning algorithm on a training set to begin the detection process. The training stage is extensive for some methods, and relatively small for others. This common training gives us an advantage when we consider the problem for the first time: we can assume that we have available to us data about a general face, and we can infer certain information regarding faces in general. The most intuitive solution to the problem of modeling faces is the geometric formulation which allows the detector to project a tested image onto 7 a learned subspace and determine whether or not it is close to that subspace. The natural thing to do with a training set, then, is to compute a manifold in Rn (from training images containing n pixels) from the most significant components of the general face. This is a very basic scheme, and is computationally burdensome. Sung and Poggio use an adaptation of this scheme to create a detection scheme using Gaussian clusters in Rn . The basic idea of their detection model is using a multiple-mean Gaussian mixture model for both objects (the general case, as opposed to faces) and non-objects. Obviously the space with low object probability is the non-object space, so it is more accurate to say that among the Gaussian object clusters, negatively weighted clusters are placed so as to improve the definition of the object space. In terms of the detection problem, these negatively weighted clusters will be centred at images which can be mistaken for faces, but are not. Their implementation uses six each of the face and non-face clusters. Their learning method is appropriate for their means: a large focus of the detector is on discerning between faces and face-like non-faces. They use a "bootstrapping" strategy for creating a non-face training set consisting of only the most meaningful non-faces (as 8 opposed to a general non-face training set, which would contain many images which are so obviously not faces that they hold little weight in the detector). Sung and Poggio construct their face set in a very straightforward manner (enlarging their data set with rotations and reflections). The bootstrapping scheme for non-face generation begins with a small set of non-face samples. Their detector is then run, and false positives are added to their non-face set. This method can be iterated until a satisfactory data set has been reached. This makes for a very time-consuming construction, but the resulting set, using their negatively weighted cluster scheme for non-faces, is well suited to their demands. If necessary, the face data set can be bootstrapped in a similar manner. Sung and Poggio claim that their system can be made arbitrarily robust in this manner: "Both false positive and false negative detection errors can be easily corrected by further training with the wrongly classified patterns" [12]. This is in reference to error rates in training sets, and does not necessarily suggest that given time, the scheme can be improved arbitrarily for unseen data. A different approach to separating faces and non-faces in image space is 9 used by Osuna et al., and followed up with work by Romdhani et al. in [7] and [9], respectively. Both are based on support vector machines, a classification method which is the result of V. Vapnik and others at AT&T Bell Labs, notably presented in [2]. The key to the model for a support vector machine is the choice of a manifold that separates the face set from the non-face set. In [7], a hyperplane is chosen, specifically the hyperplane which maximizes minimum distance on either side. A support vector set is, roughly speaking, a set of vectors (images) which are close to this hyperplane, and can therefore be used on their own to reacquire the hyperplane. In [9], an attempt to improve the performance of a similar system is made via reduced set vector machines. The methods in both papers use quadratic programming heavily, and exploit properties of their models' kernel functions. This is more closely related to their classifiers, and will therefore be left mostly to Chapter 3. In terms of training sets, Osuna et al. exploit their model and the fact that most vectors will be ignored, or at least meaningless, in their quadratic programming formulation. Because the hardware requirements for training a support vector machine in a natural way are prohibitive, training data must be chosen in a nontrivial manner. First. a set of optimality conditions, 10 specifically the Kuhn-Tucker conditions, are considered. Only those vectors which are relevant to the training, i.e. support vectors, are used. Memory requirements are quadratic in the size of this working vector set, so obviously minimizing it is key. The proposed solution is to decompose the problem into smaller sub-problems, a standard solution to such a problem when doing so is possible. Romdhani et al. [9] work further on reducing this vector set in order to improve performance. In [9], it is argued that the support vector set in detectors like the detector in [7] forms a proportion of the entire training set that stands to be reduced significantly. There has been a decent amount of research done on improving the performance of support vector machines since their development less than 10 years ago. Rhomdhani et al. apply one such method to improve the performance of an SVM-based face detector. Basically speaking, given a vector Φ in the model's feature space (expressable, thanks to the model, as a sum over the support vector set), there is a good approximation Φ to Φ. Specifically, there is a good approximation Φ which is expressable as a sum over a reduced vector set which is much smaller than the support vector set. Given a reduced set, the problem remains to minimize the norm of Φ − Φ . This can be done in terms of the model's associated kernels. 11 Akin to Sung and Poggio's bootstrap approach is the retraining performed in [9]. The positive results of such retraining are demonstrated in the context of a neural network-based detector in [10]. Schneiderman and Kanade propose a statistical model in [11]. To apply statistical methods to the problem, they represent visual attributes with wavelet coefficients. This method suits their needs because unlike other methods, with wavelets an image can be perfectly reconstructed from its transform with a coefficient set that has the same size as the image itself. Specifically speaking, their method uses three filter levels, giving 10 image sub-bands. This representation allows them to jointly model image data which is localized in space, frequency, and orientation. From this information, then, they are able to construct a histogram-based face detector. This method requires that initial histograms be constructed. Schneiderman and Kanade's approach to this is similar to the approach of Sung and Poggio's, and is in fact, loosely speaking, a statistical analogue of the bootstrapping method described previously [11, 12]. Rather than giving every training example acquired through bootstrapping equal weight, they use an approach for faces that explicitly minimizes error in the training data. This 12 is done using AdaBoost, an algorithm for converting a weak learning method into one with high accuracy [4] (Viola and Jones' detector uses a boosting algorithm which is based on AdaBoost). In their training method for faces, Schneiderman and Kanade begin with a bootstrapping basis which is evenly weighted, then give more weight to training images which are identified as false positives. Just like Sung and Poggio's bootstrapping, this training can be iterated to improve robustness. In [10], Rowley et. al. present a face detection system based on artificial neural networks. This paper seems to have become an early standard in face detection, against which many researchers compare their results. Of course, this fact may be contributed to by the fact that Rowley provided several authors with test data [9, 13]. The neural network is the most novel part of the paper, as the general method for detection is fairly standard, in terms of scanning over every pixel at various scales. The neural network contains three types of hidden units: one set of units for quadrants of the 20 × 20 image, one set for quadrants of the quadrants, and one set for looking at overlapping horizontal strips of the image. The idea is clear: certain hidden units will help detect certain facial character- 13 istics. For example, since an oval binary mask is applied to the image in preprocessing, dark corner pixels will likely be removed in the case of a face. In this situation the quadrant hidden units are likely to sense the presence of eyes in the upper two quadrants. In order to train the neural network on a face data set, a large number of face images were used, in which feature points were labeled manually [10]. The locations of these feature points are averaged over the training set, then warped to coincide with predetermined points. Each face training image can then be aligned to the mean as the optimal solution to an overdetermined system. Iterating this method results in a suitably warped data set. This set is artificially enlarged as in other methods through rescaling, rotation, reflection, and translation. The result of this data set enlargement is that the neural network, as a filter, becomes invariant to these transformations within a range. Sung's bootstrapping method is used to determine a non-face data set. Rowley et al. provide interesting classification methods, which will be discussed in Chapter 3. Papageorgiou, Oren, and Poggio, in what can be considered to be a conceptual precursor to the work of Viola and Jones, use Haar wavelets to create 14 an overcomplete representation of the face class [8]. The focus of their paper is on the development of their wavelet model. They provide a simple application of this model (for objects in general) to face and pedestrian detection. They use an extension of two-dimensional Haar wavelets called the quadruple density transform to create their redundant representative set. This initial set consists of 1734 coefficients for vertical, horizontal, and diagonal wavelets at scales of 2 × 2 pixels and 4 × 4 pixels. To avoid prohibitive computational costs in training the classifier, this set is reduced to a set of 37 significant coefficients through statistical analysis. Again, training is done using bootstrapping methods, as in [12, 10, 7, 9, 11]. In this case, Papageorgiou et al. train their system using a variety of penalties for misclassification [8]. Their results show a marginal improvement when the penalty for missed positives is an order of magnitude greater than the penalty for false detections. In practice, however, it seems like there would be very little difference between the system under the various training schemes. Following on the work of Papageorgiou et al., Viola and Jones present a much faster detector than any of their contemporaries [13]. The performance 15 can be attributed to the use of an attentional cascade, using low-featurenumber detectors based on a natural extension of Haar wavelets [5]. The cascade itself has more to do with their classifier than with their model, so it will be discussed in the next chapter. Each detector in their cascade fits objects to simple rectangular masks, basically speaking. In order to avoid making many computations when moving through their cascade, Viola and Jones introduce a new image representation which they call an integral image, which is just what it sounds like. For each pixel in the original image, there is exactly one pixel in the integral image, whose value is the sum of the original image values above and to the left. The integral image can be computed quickly, and drastically improves computation costs under the rectangular feature model. As explained in [13], the integral image allows rectangular sums to be computed in four array references. This is easy to see when the model is considered; under the conventional representation of an image, the computation time needed would be proportional to the size of the rectangle. At the highest levels of the attentional cascade, where most of the comparisons are made, the rectangular features are very large. As the computation progresses down the cascade, the features can get smaller and smaller, but fewer locations are 16 tested for faces. Thus the advantage of the integral image representation is clear. The remaining difficulty lies in creating and training the attentional cascade, which also lends very heavily to the detector's efficiency. Training the attentional cascade is similar to the other training methods seen, obviously adapted to suit the situation. Because of the cascade's nature, a very high detection rate is needed, but the false detection rate can also be very high, as the overall figures decrease exponentially with the figures for each individual cascade level, based on the depth of the cascade [13]. Each level of the cascade needs to reject examples that are closer to faces than the previous level (as each level inherits the previous level's accepted images). Viola and Jones therefore pass a large number of non-face examples to train the first cascade level, then pass those detected by the first level on to the next level, and so on. For face training, each level is trained on the same face set. This method is similar in spirit to the more basic bootstrapping methods adapted from Sung's method, but is geared toward the progressive nature of the attentional cascade. 17 Chapter 3 Classifiers Each model requires a classifier to determine whether given data are faces or non-faces. The classifier is, in general, some threshold applied to the data, usually some sort of goodness-of-fit measure. The classifiers for the models in Chapter 2 are discussed in this chapter. Recall that Sung and Poggio model their face likelihood with Gaussian clusters and anti-clusters in Rn (n, in their case, happens to be 283) [12]. In their implementation, six clusters and six anti-clusters are used. Obviously the number of clusters, and to a lesser extent the number of anti-clusters, will have a great effect on the receiver operating characteristic (ROC) curve. The numbers of clusters (i.e. the classifier architecture) were determined 18 empirically. This detector was tested for a number of different architectures, and the "six and six" architecture provided the best results. The Gaussian clusters used are non-isotropic, that is, the axes of each cluster are not of equal length. Sung and Poggio justify this under the belief "that the actual face distribution can be locally more elongated along certain vector space directions than others" [12]. This seems like a reasonable generalization, but it leaves us with the problem of choosing a suitable distance function. A natural choice for a model based on these non-isotropic clusters is the normalized Mahalanobis distance. The normalized Mahalanobis distance between an image under consideration x and the centre µ of a Gaussian cluster is 1 Mn (x, µ) = (n ln 2π + ln |Σ| + (x − u)T Σ−1 (x − u)), 2 (3.1) where Σ is the covariance matrix of the Gaussian cluster [12]. We can see that if the model contains a single Gaussian cluster, then thresholding at a fixed Mahalanobis distance from µ selects all vectors (images) which are within a fixed probability density in the model. Of several distance metrics tested for this model, a two-value combination yielded the best results. For a given vector, these two values are obtained for each cluster. The first, D1 is the Mahalanobis distance between the vector and the cluster centroid after 19 both have been projected to the space of the cluster's 75 most significant eigenvectors. The second, D2 , is the Euclidean distance between the vector and its projection to this 75-dimensional space, i.e. its out-of-subspace error. For each cluster, then, this vector has a two-value distance. These are given a weighted sum and checked against a threshold to determine whether the vector is a face or not. Relative results for this particular classifier and its variants are discussed in Chapter 4. In terms of preprocessing work, Sung and Poggio perform the standard operations: image resizing, illumination gradient correction, and histogram equalization. Further, they mask the 19 × 19 pixel images, removing some border and especially corner pixels from consideration. Osuna et al. perform identical preprocessing for their support vector machine detector [12, 7]. For the support vector machine detectors, the obvious desire is to have faces on one side of the selected hyperplane and non-faces on the other side. This is the ideal classifier for the model. After training, the system is very similar to that of Sung and Poggio [7]. The simplicity of the classifier's criterion for support vector machines makes the run-time computation of the methods in [7] and [9] extremely simple. Pre-processing of tested images must be performed, but in general, these two methods give impressive 20 run-time computational savings (run-time complexity for these machines is proportional to the size of the support vector set [9]. As training is the crux of both support vector methods, the classifier is of relatively little interest in contrast to the training algorithms themselves. Schneiderman and Kanade, for their classifier, use 17 statistical image attributes, some of which relate to only one sub-band, and some of which relate to several. Recall that the sub-bands represent different frequencies, orientations, and spaces. This means that sub-bands, when sampled to form an attribute, can interact in a number of different ways. The detector samples each of these 17 attributes over the object. Obviously some attributes will contribute to detecting a face more than others, e.g. the eyes and nose are more significant than the chin [11]. Their classifier thresholds a pattern's likelihood ratio, i.e. a threshold λ is chosen such that faces are exactly those regions for which x,y∈region x,y∈region 17 k=1 17 k=1 Pk (patternk (x, y), x, y | object) Pk (patternk (x, y), x, y | non-object) > λ, (3.2) which is a very natural value to threshold. The run-time calculations needed for this scheme are extensive, so a heuristic coarse-to-fine strategy is used, first thesholding values for level 1 wavelet coefficients, then further threshold21 ing values for level 1 and 2 coefficients for areas not rejected, then performing the final classifier on the remaining regions. Rowley et al. use arbitration between multiple neural networks to eliminate many of their false positives. However it is first important to understand the classification criteria for a single neural network as implemented in [10]. Back-propagation with momentum is used as the networks' training algorithm, and the training is done iteratively. This will result in networks that are self-programmed to classify faces versus non-faces [1]. This is the beautiful part of this detector. What Rowley et al. do to reduce error after passing images through neural networks is twofold. The first heuristic used is based on the observation that false positives have overlapping multiple detections less frequently than do true faces. The merging step of the classifier demands that true faces must have a certain number of overlapping detections. These detections are projected over various image scales in the image pyramid and a weighted centroid is computed. The result is a single detection where there once were many (and, subsequently, fewer false positives). The second step of the classifier involves arbitration between multiple networks. Because the networks are trained with random initial variables, there 22 is nondeterminism among networks trained in the same manner. Several methods were tested for successful arbitration: heuristics involving logical operations, and a separate neural network, itself designed to arbitrate between several networks. All of these arbitration methods work well; extensive result tables are given in [10], and will be discussed in Chapter 4. Preprocessing is explained thoroughly in [10]. Once an oval mask has been applied to the image, a linear best-fit function is calculated and subtracted from the image to correct lighting conditions. Histogram equalization is then performed. This step sets contrast and compensates for camera variants. This detector, like others, implements a coarse-to-fine formulation to improve performance. The combination of the detection and error prevention methods in [10] makes for an impressive detector, as will be outlined more clearly later on. It is no wonder that this paper is regarded as a standard against which new detectors are measured. Papageorgiou et al. use a support vector machine, as in [7, 9] for their classifier, due to the fact that such machines allow small parameter count and minimized generalization error, a concern which arises in [12] in the context of model architecture (this is a global concern, assuming the absence of a 23 complete data set). In fact, Papageorgiou et al. create a reduced coefficient set which is akin to the support vectors in [7], in the sense that a small subset of training data can be used to accurately represent the relationship between faces and non-faces. In this paper, however, the focus is not in the implementation (i.e. the classifier), but rather on the value of the overcomplete set of wavelet coefficients in representing complex object classes, specifically the classes of faces and pedestrians [8]. Viola and Jones use a classifier that, largely for the sake of computational efficiency, is based on an attentional cascade. The individual weak classifiers are based on a variant of the AdaBoost algorithm, which converts weak classifiers into a strong classifier via boosting. To be detected, an image must be detected by each level of a series of basic classifiers, each more discriminating than the last. The computational advantage is gained in the fact that the initial levels of the cascade can use very simple features for their classifiers, and therefore can reject the vast majority of locations in an image quickly. By the time the cascade levels become more meaningful, they are operating only on a small proportion of the initial image locations. In their implementation, Viola and Jones use a 10-layer cascade, each of which 24 contains 20 rectangular features. They compare this against their initial, less efficient detector, which uses 200 rectangular features. One effect of the cascade strategy is that each classifier must have an extremely high detection rate, but can get away with false positive rates that would in other circumstances be thought abysmal. The reason for this is not hard to see: The false positive rate F of the entire K-layer cascade is K F = i=1 fi , (3.3) where fi is the false positive rate of the ith classifier. Similarly, the cascade's detection rate is K D= i=1 di , (3.4) so the unusual restraints on detection and rejection rates are obviously justified [13]. More detailed analysis and research regarding sequential testing is done by Fleuret and Geman [3]. Their model is a statistical approach, like Schneiderman and Kanade's in [11], but their focus is on theoretical work regarding cascades. 25 Chapter 4 Results and Conclusions 4.1 Results Viola and Jones easily present the best results in terms of computation time. In terms of their error rates, they provide impressive ROC curves and numerical figures that rival those of Rowley et al. [13]. Rowley et al. provide the most extensive test data of all papers addressed, and reach very impressive results through their merging and arbitration methods [10]. With their six cluster and six anti-cluster architecture, Sung and Poggio reach fairly good results, while numerically, Schneiderman and Kanade boast what seem to be the best numerical results [11]. Osuna et al. attain slightly better rates than 26 Sung et al. [7], and Romdhani et al. manage to vastly improve the speed of a support vector machine with only marginal loss in classification accuracy [9]. An interesting point to make is that while Schneiderman and Kanade only train their detector on front and profile face poses, the structure of faces aids the detection of partially averted faces: in some of the detected profiles in [11], this effect is noticeable. The reason for it can be seen if only the selected image window (a pentagon) is viewed. In some cases where the face is almost front-facing, half of the face, when viewed alone, looks very much like a profile. In this case, it doesn't seem like more than three poses are necessary. 4.2 Conclusions and Future Work Despite the broad range of general approaches, several aspects seem to be particularly effective in face (and in general, object) detection schemes. Sung's bootstrapping method for training detectors is very effective, and the reasons are clear; it is important to best define those areas in the border between faces and non-faces when classifying a window. Also evident is the fact that 27 due to the nature of the problem, classifier cascades are necessary in order to attain computationally cheap detection. Since the vast majority of pixels in a given image will represent non-face windows, it is very important that these pixels be rejected with as little computation as possible. Viola and Jones seem to have the best application of this principle, and it is aided by the fact that their wavelet representation of their classifiers is flexible enough to perform meaningful rejection with very little cost. In this sense, the integral image is absolutely key to a fast application of Haar wavelets. While Rowley, Baluja and Kanade's neural networks approach performs well and is beautiful in the sense that neural networks give such a conceptually natural simulation of human detection, the speed of such a scheme must be improved dramatically if it is to compete with the wavelet formulation. It seems unlikely that a detection scheme that does not use an easily decomposable model will move forward in the same way that wavelet applications seem able to. One obvious avenues for future research is model combinations, since weak classifiers can be used to quickly reject large portions of an image with an effective false negative rate of 0. After such rejection, a more powerful classifier could be used to scrutinize remaining areas. 28 It would be interesting to see the improvement in performance upon applying the integral image formulation to other Harr wavelet-based detectors, such as Papageorgiou et al. [8] and Schneiderman and Kanade [11]. In the same vein, it would be interesting to see a more powerful cascading scheme applied to the methods of Viola and Jones [13]. The work of Viola and Jones opens the way for further practical applications to face detection. One immediate such application would be buttressing face tracking methods. Running at 15 frames per second, a detector could add robust backup to a tracker. Furthermore, the integral image is a breakthrough in wavelet classification that can easily be seen to generalize well to other object classes. 29 Bibliography [1] C.M. Bishop, Neural networks for pattern recognition, Oxford University Press, Oxford, 1995. [2] Corinna Cortes and Vladimir Vapnik, Support-vector networks, Machine Learning 20 (1995), no. 3, 273–297. [3] Francois Fleuret and Donald Geman, Coarse-to-fine face detection, International Journal of Computer Vision 41 (2001), no. 1/2, 85–107. [4] Yoav Freund and Robert E. Schapire, A decision-theoretic generalization of on-line learning and an application to boosting, European Conference on Computational Learning Theory, 1995, pp. 23–37. [5] S. Mallat, A wavelet tour of signal processing, Academic Press, San Diego, 1998. 30 [6] Yoshio Matsumoto and Alexander Zelinsky, Real-time stereo face tracking system for visual human interfaces, Proc. Int'l Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time (1999), 77–82. [7] E. Osuna, R. Freund, and F. Girosi, Training support vector machines: An application to face detection, 1997. [8] C. P. Papageorgiou, M. Oren, and T. Poggio, A general framework for object detection, Proceedings of International Conference on Computer Vision (1998), 555–562. [9] S. Romdhani, P. Torr, B. Scholkopf, and A. Blake, Computationally efficient face detection, Proc. Int. Conf. on Computer Vision (2001), II:695–700. [10] Henry A. Rowley, Shumeet Baluja, and Takeo Kanade, Neural networkbased face detection, IEEE Transactions on Pattern Analysis and Machine Intelligence 20 (1998), no. 1, 23–38. [11] H. Schneiderman and T. Kanade, A statistical approach to 3d object detection applied to faces and cars, IEEE Conference on Computer Vision and Pattern Recognition - to appear (2000). 31 [12] Kah Kay Sung and Tomaso Poggio, Example-based learning for viewbased human face detection, IEEE Transactions on Pattern Analysis and Machine Intelligence 20 (1998), no. 1, 39–51. [13] Paul Viola and Michael Jones, Robust real-time object detection, International Journal of Computer Vision - to appear (2002). 32
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Highlight Realty
I will be glad to help!
Thank you, Karina Leal
Leal USA REalty
I will be glad to help!
Thank you, Karina Leal
Leal USA REalty
In the meantime, the two best gauges are a CMA by your Realtor, and an Appraisal.
Good luck and may God bless
Good luck!!

subset: commoncrawl


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Nicolas Winding Refn's critically-acclaimed Neo-Noir flick, Drive, has not been a huge hit at the box office – and is (bizarrely) at the center of a lawsuit over false advertising – but because of that movie, more people are now interested in hearing about whatever project Refn gets up to next, especially his new take on Logan's Run.
Refn's Drive leading man, Ryan Gosling, is also set to headline the Logan's Run remake. While there's no set production timetable for the project just yet, well-regarded scripters like Alex Garland and Will Beall have already been recruited to work on the screenplay.
Brief bit of history: Authors George Clayton Johnson and William F. Nolan's original 1967 Logan's Run novel was previously adapted into a cult classic 1976 sci-fi film that deviated significantly from its inspiration. The story was also the basis for a short-lived TV series spinoff that ran from 1977-78 and gave rise to both Marvel and Malibu comic book adaptations several years later.
The original Logan's Run book takes place in a dystopian futuristic society where people are required to die at age 21, in order to prevent overpopulation. Plot-wise, the novel revolves around Logan-6, a "Sandman" or government agent assigned to track down and kill "runners", ie. those who refuse to comply with the lethal demands of society… that is, until Logan falls in love with a woman named Jessica and begins to question the very system he swore to serve.
Refn's Logan Run is expected to by and large retain that setup – though, one of the ways it reportedly "updates" the story is by raising the "age limit" to 30.
You've probably already noted the narrative similarities between Refn's Drive and Logan's Run. Case in point: the latter, like the former, features a protagonist (to be played again by Gosling) whose stoic manner and methodical lifestyle is disrupted by a femme fatale – one who reawakens the young man's sense of humanity and inspires him to protect her from the dark and dangerous world that surrounds them… violently, if needs be. So, in that sense alone, this project reads as a promising fit for Refn's creative sensibilities.
Another encouraging note: Refn has demonstrated himself to be an auteur who leaves a recognizable artistic fingerprint on each of his films (see: Drive, Bronson, Valhalla Rising, etc.). So, Refn's cinematic take on Logan's Run will almost certainly feel largely like his own personal interpretation of the original literary source material (a la the Coen Brothers' True Grit) rather than a remake of a previous film adaptation.
We will continue to keep you posted on the status of Logan's Run as more information is released.
Source: THR


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With over 25 Shops under the one roof, The Centenary Centre provides customers a wide selection of antique furniture, art, ceramics, deco, retro, jewellery, glass, militaria, linen, toys, ephemera, tools, books and a huge variety of collectables from the 1780's to the 1980's.
Discerning collectors as well as fashionable home decorators will find the centre a delight. There is also an eclectic mix of modern, designer and stunning antique jewellery, as well as a Vintage Grocery Store Museum
Art, Cameras, Ceramics, China, Clocks, Clothing, Collectables, Diamonds, Ephemera, Furniture, Glassware, Jewellery, Kitchenalia, Kitchenware, Lamps, Mirrors, Pearls, Plates, Pottery, Tins, Tools, Toys
Architectural, Australian, English, French
Art Deco, Australiana, Colonial, Edwardian, Retro, Victorian
Brass, Cedar, Crystal, Pine, Silver
Antiques Newcastle, Antique Jewellery, Antique Jewellery Newcastle, Antique Collectables Newcastle, Antique Collectables, Retro Clothing, Retro Clothing Newcastle, Antique China, Antique China Newcastle, Antique Clocks


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Literature: Necessary Evil
The third and final book of The Milkweed Triptych.
Necessary Evil contains examples of:
- Alternate History: Another alternate history - an in-universe alternate timeline from the alternate history of Bitter Seeds. In this one, Gretel makes sure the war mostly plays out like in our history.
- Alternate Timeline: Gretel's plan was to create a timeline in which the Eidolons do not kill her or humanity.
- Bittersweet Ending: The warlocks are dead and humanity is saved. Marsh-2 gets to live out his life with Liv and their daughter. Marsh-1 however has to go into hiding alone overseas as he's a wanted man, and Will has been murdered by Gretel.
- Brought Down to Normal: Gretel, and twice to add insult to injury; once, when the interference of two timelines stops her predicting that Liv would be rescued from the bombing of Coventry, and finally when she has her wires removed by both Marshes at the end of the story.
- Character Tics: Marsh1 eventually gives himself away to Will by his habit of cracking his knuckles against his jaw.
- Go Mad from the Revelation: Gretel, when she realizes that she no longer has perfect control of the timeline.
- Historical In-Joke: Gretel is apparently responsible for the Germans' slow response to the Dunkirk evacuation, and for otherwise making sure the Second World War actually happens in the way we remember it happening.
- Madness Mantra
- I Reject Your Reality: After 7000 heartbeats in close proximity to an Eidolon, Marsh2 starts losing his grip on how reality actually works.
- I Want My Beloved to Be Happy: Marsh1 forgoes life with Olivia so that Marsh2 will have the happy marriage they never had.
- Kick the Son of a Bitch: Gretel's exile; the island is too windswept to allow wildflowers to grow (Gretel's hobby), and the last words of both Marsh's is to inform Gretel that her brother Klaus is dead.
- This Cannot Be!: Gretel suffers a Villainous Breakdown on discovering Liz survived the bombing of Coventry.
- The Mole: Will becomes this for Marsh1 in Milkweed.
- No Yay (In-Universe) whenever Gretel hits on either Marsh.
- My Future Self and Me: 2 × Raybould Marsh.
- Nice Job Breaking It, Hero: Marsh1 misses a chance to contact Will because he turns up at the police station in response to a call that his billfold has been stolen, tells the police it must be a practical joke (as he still has his 1940's billfold), then leaves without even looking at the mysterious stranger who was caught with it. His Milkweed boss tears strips off him for this when it's later assumed that Marsh1 is a German spy. Marsh1 later sleeps in, missing his second and last chance to intercept Will before he recruits the warlocks.
- Reality Warper: The Eidolons. Shown in detail when Will summons an Eidolon for Marsh2 in Berlin.
- Sealed Room in the Middle of Nowhere: At the end of the book Gretel is abandoned on a tiny windswept island off the Scottish coast, with her food being resupplied every six months.
- Set Right What Once Went Wrong
- Stable Time Loop: ... sort of. When Marsh1 tries to shoot Marsh2 in the knee and fails, their knee pain suddenly goes away.
- Tele-Frag: Marsh1 kills the twins this way.
- Time Travelers Are Spies: Marsh1 ends up in wartime London with another man's wallet and no period currency. Naturally, he's suspected of being a German spy.
- Trust Password: Needed to enter Milkweed. Fortunately for Marsh1, they're the same as in his timeline.
- The Uriah Gambit: Marsh1 steals the blood samples of the warlocks and puts it in the box uses for the teleportation, so they'll be unexpectedly transported to the war zone where he can more easily arrange their demise.


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April Beauty Time and Health SpaRead MoreFrom the soft pillows on the wicker furniture to the luxurious drapes that conceal private treatment rooms, April Beauty Time and Health Spa is clearly a place intended for relaxation—for guests. The spa's aestheticians, however, are models of productive activity, working to beautify clients' faces and skin with waxing and skincare services or to rid bodies of excess fat cells with contouring treatments.8405 N HIMES AVE STE 106TAMPA, FL US
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Carrabba's Italian GrillRead MoreA pasta-lover's paradise, Carrabba's Italian Grill is the perfect place to see and be seen — this chic restaurant serves Italian food with a twist. Delectable pizzas and pastas feature prominently on the restaurant's menu. Both low-fat and gluten-free options are available here. Be sure to complete your meal at Carrabba's Italian Grill with a drink from the restaurant's full bar. Enjoy the beautiful weather while you chow down — with outdoor seating, Carrabba's Italian Grill is a great summer destination. Carrabba's Italian Grill will be able to accommodate your large party. Guests may have a hard time conversing, as the restaurant is rather noisy. Lines can get long with no reservations, so be sure to plan for an early arrival. No need to put on airs for a trip to Carrabba's Italian Grill — the dress code and ambience at this restaurant are totally laid-back. For those in a rush, the restaurant lets you take your food to go. Impress the visitors at your next gathering by calling in Carrabba's Italian Grill for catering. Free parking is available for patrons who dine at Carrabba's Italian Grill. A meal at Carrabba's Italian Grill will typically set you back about $30.11435 N Dale Mabry HwyTampa, FL US
Ingram's KarateRead MoreEduardo Torres's interest for capoeira began in his teens, but it wasn't until he traveled from Northern California to Florida that he discovered his passion for teaching the Afro-Brazilian sport. After extensive training, Eduardo earned the title of Professor Girino and became a member of Grupo Maculelê. Tucking that experience into his back pocket, Eduardo now leads four Tampa Capoeira studios across the Greater Tampa Bay Area. At those studios, Professor Girino and his savvy staff teach the ways of capoeira to students of all ages and skill levels, and they have even trained Major League Baseball catcher Russell Martin. During classes, students form a traditional roda, or circle, as they learn everything from the rhythmic chants that keep fighters on beat to the fluid, acrobatic movements that send their bodies spinning across a mat. Professor Girino also points out that capoeira is not about fighting but rather anticipating the opponent's next move, much like playing chess against a short-tempered orangutan.14457 N Dale Mabry HwyTampa, FL US
Kobe' Japanese Steak HouseRead MoreFor fresh maki, Tampa's Kobe' Japanese Steak House has got you covered. The gluten-free and low-fat fare at Kobe' Japanese Steak House will leave you happy and full. Drinks all around! Pair your dinner with a beverage from Kobe' Japanese Steak House's full bar. Kobe' Japanese Steak House is more than willing to accommodate families, so kids are welcome to tag along. Groups of all sizes can easily be seated at Kobe' Japanese Steak House. Casual dining at its best, Kobe' Japanese Steak House customers are free to enjoy themselves in jeans and a T-shirt. Catering is also available if you'd like to serve Kobe' Japanese Steak House's tasty dishes at your next party. You can also grab your food to go. The restaurant offers free parking in the lot next door. Kobe' Japanese Steak House's mid-priced fare will typically cost you about $30 per person or less.14401 N DlTampa, FL US
Royal Pets Market & ResortRead MoreSome customers choose from a colorful array of cookies, donuts, and other delectables on a tiered and crystal-encrusted dessert tray, while others relax and enjoy floor-to-ceiling murals of a picturesque countryside in the indoor dog park. None of them, however, happen to be human—such is the focus on luxury at Royal Pets Market & Resort, where boarding, grooming, training, and adoption services are overseen by an experienced staff. After pampering treatments such as aromatherapy baths or moisture-therapy wraps, dogs and cats can be outfitted from the wide selection of collars, foods, toys, and apparel in the expansive store.16010 Mapledale DriveTampa, FL US


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This item can only be shipped within the 48 contiguous states via Standard Ground Shipping. In order to return this item for a refund or replacement, all fuel must first be drained.
(based on 25 reviews)
Ratings Distribution
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of respondents would recommend this to a friend.
Best Uses
Most Liked Positive Review
Very good for the price
A second ago in the Best Uses I said it was good for a minibike with a few exceptions. If you cant make you're own throttle linkage (You have to be pretty creative)Then...Read complete review
A second ago in the Best Uses I said it was good for a minibike with a few exceptions. If you cant make you're own throttle linkage (You have to be pretty creative)Then buy the 212cc motor, I comes with a throttle linkage already installed.
Most Liked Negative Review
Only 1 complaint
Nothing special but it does the job. I have the 99cc model and have used it for a little over a year. I use it for my pest control business as a primary engine...Read complete review
Nothing special but it does the job. I have the 99cc model and have used it for a little over a year. I use it for my pest control business as a primary engine to run my pump for exterior treatments. There is a lot of vibration at low rpms but not to the point that I have any problems. It runs good, starts easily, and does what I need it to do. My only complaint is the gas cap. It is a two piece cap made from metal with a plastic cover. After 2 or 3 fill-ups the plastic part that you turn separated from the metal part that seals the top of the tank. It is still usable but difficult to get on and off. I have tried to fix it but have not had any luck. I just use the metal part and complain to my self every time I fill it.
Reviewed by 25 customers
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3 hp motor
By Art
from Ontario Canada
About Me Avid Do-It-Yourselfer
Comments about Predator Engines 3 HP (79cc) OHV Horizontal Shaft Gas Engine EPA:
Bought this engine to replace an electric motor on a piston water pump. I have a cottage in the bush on island with no power. The engine does a great job of running the pump and I use it to fill a 300 gal tank. I was all as advertised and ran right out of the box. Great price and value.
Bottom Line Yes, I would recommend this to a friend
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Comment on this review
Replacement engine for McLane Tiff mower.
By Johnny B. Goode
from Mariicopa Az
Had a 30yr old McLane tiff mower I couldn't get parts for engine. Bought 3hp Predator to replace it. Only had to use a couple of washers on each mounting bolt to raise engine up to match pulley position. Runs like a new mower now, starts up on a couple of pulls everytime.
Images shared by Johnny B. Goode
Ready to go now.
(0 of 1 customers found this review helpful)
3HP Predator
By pakroger
from South Dakota
I put this motor on my old snapper tiller. It bolted up great, the motor started up great makes the tiller seem like new.
(1 of 2 customers found this review helpful)
Exelent and good price.
By Ric, cabinet maker
from Los Angeles, CA
About Me Casual Do-It-Yourselfer
I use for a air compressor what I built, and work perfect, thanks Harbor Freight Tools
Images shared by Ric, cabinet maker
From electrical to gas
Tags: Picture of Product
(3 of 4 customers found this review helpful)
Very good motor.
By Hall
from Guin,al
About Me Professional
We put these motors on all our tillers and never had 1 come back bad yet.
(4 of 4 customers found this review helpful)
By danxbt
from Schererville, IN
Bought this as a replacement engine for my son's mini bike. Out of the box it bolted in perfectly and started on the first pull and has ever since.
(4 of 5 customers found this review helpful)
Reliable and spark plug removes easily
By Dave
from East Aurora, NY
Bought this to fit on an edger, had to fabricate a plate to match the edger's old holes. A review here says the muffler needs to be removed to remove the spark plug; not true, a spark plug wrench removes it just fine (if you live near a store, look at their demo to see for yourself). Has a plastic flywheel like virtually any knockoff engine I've seen, hope it holds up.
(5 of 7 customers found this review helpful)
Direct Fit for JD 216 Walk Behind Tiller
By Mike W.
from Cumming, GA
This motor is a direct fit replacement for the 2HP OEM (B&S) motor on my John Deere 216 Walk Behind Tiller. It took only 45 minutes to remove the old motor and replace it with this one. Hardest part of the whole operation was removing the pulley from the old motor (Rotor puller worked great for this). Once removed the pulley fit right onto the 5/8" keyed shaft (key is removable if necessary). Once I filled it with oil and gas it started on the first pull. Well done!
(9 of 10 customers found this review helpful)
greta value for the buck
By Dennis
from Winter Haven, Fl.
I purchased the 3HP engine for my Botac edger. It was easy to install with few, very easy, alterations. Cranked at first pull, runs quiet. Replaced a Briggs 3HP 30+ years old.
(14 of 15 customers found this review helpful)
By Crazy legs
from Fort Worth Tx.
Most orders will be processed and leave our warehouses within 1-2 business days from the time your order is placed. Orders placed on Saturday or Sunday will be processed on Monday.
*Overweight items are shipped via freight delivery, please allow up to 15 business days for shipping. Standard Ground Shipping rates apply to deliveries within the continental Unites States.
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35 points
More About Points »
Florence, SC
Recent Activity
Question Asked:
Receiving message time for regular service checkup and also multiple lights failure. Would either of these cause the car to shutdown. I was driving on the interstate when the multiple light failure kept flashing rapidly showing low beam, once I exited it was the low beam and care shut off but restarted immediately.
Question Asked:
I thought it was the battery bought a new one but car stopped again after driving about 25 miles. Message started yesterday.
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|10 BrianLankford


text: We stayed here a week. The bungalows in the nicely laid out park are spacious. Ours had a double bed and two single beds. The food was okay. Staff is helpfull. The massages in the Spa are very good, though not cheap, at 30 Euro for half an hour and 50 for an hour. Swimming pool is big and clean.... More


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25 year old woman | Crafton, PA, USA | Seeking men 24-33 within 50 miles of Pittsburgh, PA
Everything happens for a reason..
I am a very outgoing and genuine girl with a big heart. I love to have fun, be spontaneous and do the unexpected. I am currently in Pharmacy school while working in a pharmacy and in school to receive my technician license as well as being a hairstylist out of my house. I am very hard working and know what I want in life. I have my own house and very determined to get what I am working for in life.I am very close with my family they mean everything to me and are extremely important in my life. I have a puppy his name is Bruno that I love he is the cutest :) I love watching and going to sporting events any chance I can I will get tickets and go! Sometimes if I have the chance I will fly or drive to go to one!! Its just so much fun and getting away sometimes is always fun!! I am big with sports because I have played majority of my life. I also love to travel when I can and experience new things! I am a big movie person, I love movies and going to the movies but snuggling up with wine at home is always fun to. I like going out with my friends and having a good time. Have fun, laughing and smiling is always the best medicine for everything!!! I like to exercise but sometimes my schedule and studying makes me more burnt out to do so. i am just looking for someone who wants to be with me, take me seriously, take an interest in me with no games and have fun when were together!! Honesty is a big thing for me..If you are interested in getting to know me just message me and ask :)
Coffee and conversation , Dining out , Movies/Videos , Playing sports , Shopping/Antiques , Travel/Sightseeing , Watching sports , Wine tasting
Baseball, Basketball, Bowling, Football, Golf, Hockey, Running, Skiing, Soccer, Walking / Hiking
I exercise 1-2 times per week.
I have Cats, Dogs
I have a 5 month old puppy named Bruno.
Z{{Cta}} {{#if HasMoreInfo}} ?{{CtaSecondary}} {{/if}}
|What she is looking for
|5'9" (175cms)
|6'0" (182cms) to 6'5" (195cms)
|Body type:
|About average
|About average, Athletic and toned
|No preference
|No preference
|No Way
|No Way
|Social Drinker
|No preference
|No preference
I work in a pharmacy while I am in school for Pharmacy and school for my Technician License and I am a hairstylist out of my house.
|I'll tell you later
|No preference
|Never Married
|Never Married
|Have kids:
|Wants kids:
|Definitely, Someday
|White / Caucasian
|White / Caucasian
|Christian / Catholic
|No preference
|English, Italian, Other
|I'll tell you later
|High school, Some college, Associates degree, Bachelors degree, Graduate degree, PhD / Post Doctoral


text:
By Rob Blackwelder on Tuesday 8th March 2005
Re-enforcing their stuck-in-B-list status, Kim Basinger and Jimmy Smits star this week in a laughably gothic second-coming chiller, "Bless the Child," which once again commandeers Catholic dogma as a jumping-off point for a half-witted, high-gloss horror movie.
Like "Stigmata" and "End of Days" before it, "Bless the Child" invents its own "previously undiscovered" Biblical mythology to propel its story about a battle for the soul of an abandoned 6-year-old girl (Holliston Coleman) named Cody, who -- it is implied -- is the reincarnation of Christ.
Kim Basinger plays her aunt Maggie, a New York City psychiatric nurse who's strung-out younger sister (Angela Bettis, "Girl Interrupted") drops the infant girl on her doorstep and disappears. Maggie -- an agnostic, as all religious chiller heroes are at first -- raises Cody and gradually begins to realize (much more gradually than the audience) that the child has supernatural gifts. Rocking back and forth while ain't-it-eerie monk chants reverberate on the soundtrack, Cody makes plates spin with telekinetic power, lights candles just by staring at them intently and brings back to life pigeons that smack into windows.
Meanwhile, a serial killer is on the lose in Manhattan, performing ritual murders on kids with Cody's birthday, and we're treated to the abduction of one of them by a menacing bald guy with beady eyes, a black van and a generic troubled punker from central casting as his sidekick.
When Cody's mom turns up again on the arm of Eric Stark (Rufus Sewell) -- a rich and famous, demonic-looking self-help cult leader -- demanding to take Cody back, it's no surprise to discover her dubious new husband is connected to the kidnap-killings, and even less of a surprise to discover he's a servant of -- you guessed it -- Satan.
How anyone can keep a straight face while making a movie like this is beyond me. The loophole-riddled story only stays afloat because Stark is too stupid to just off Aunt Maggie after kidnapping Cody, leaving her free to mess up his plans for converting the little girl so his master can take over the world -- or something like that. (When the Satanists finally do try to kill Maggie, it is, of course, in ridiculously complex ways.)
The dialogue is embarrassing ("She will be ours," Stark curses at the sky after a demonstration of Cody's saintliness). Stark's minions are antiquated stereotypes (Cody's evil nanny, who kills people with knitting needles, looks like a dried-up, Victorian Morticia Adams). And director Chuck Russell ("Eraser," "The Mask") shamelessly pads "Bless the Child" with every hackneyed demonic and religious symbol he can muster, including pitchfork tattoos, gratuitous gargoyles, demons generated with comically cheap CGI effects and the return of the Star of Bethlehem.
The movie even draws to a close with a fire-and-brimstone ritual sacrifice at a spooky, boarded-up mansion.
Coming off an overly-earnest performance in "I Dreamed of Africa," Basinger continues to prove her Oscar win for "L.A. Confidential" was a fluke, bringing a lot of whining but zero charisma to the lead role here.
Smits -- playing an FBI agent (and former seminary student) who believes Maggie's Satanic tale -- has something of an excuse for appearing in "Bless the Child." Trying to break away from television, he's landed unceremoniously on the David Caruso career track. After this flick, he should be crawling back to TV soon enough.
As for the presence of proven talents like Ian Holm (as a rebel ex-priest "who was censured by the Vatican") and Christina Ricci (as a heroin-addicted street punk and Stark cult escapee), I can only assume Paramount Pictures is holding over them some pretty impressive blackmail material.
Year: 2000
Run time: 107 mins
Box Office USA: $28.1M
Distributed by: Paramount Pictures
Production compaines: Paramount Pictures, Munich Film Partners & Company (MFP) GHS Productions, Icon Entertainment International
Contactmusic.com: 1 / 5
Rotten Tomatoes: 3%
Fresh: 3 Rotten: 109
Director: Chuck Russell
Starring: Kim Basinger as Maggie O'Connor, Angela Bettis as Jenna, Holliston Coleman as Cody, Rufus Sewell as Eric Stark, Christina Ricci as Cheri Post, Jimmy Smits as Agemt John Travis, Michael Gaston as Det. Frank Bugatti, Lumi Cavazos as Sister Rosa, Dimitra Arliss as Dahnya, Eugene Lipinski as Stuart, Anne Betancourt as Maria, Ian Holm as Reverend Grissom, Helen Stenborg as Sister Joseph, Matthew Lemche as New Dawn Kid at Van, Dan Warry-Smith as New Dawn Kid


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Paul McCartney Remembers MJ While Katy Perry Sort of Doesn't Remember Paul
by Mike Stanz
posted Jun 30 2014 5:00AM
This is from a couple of weeks ago, but it's a neat little video clip. Katy Perry and Paul McCartney (who ever thought they would ever share a couch?) were guests on the BBC's
Graham Norton Show
Katy was trying to salute Paul, but she stumbled a little when she got to "… and the fact that you're still here today…" Pretty funny the way it worked out.
And then Paul tells a great story about meeting and working with the King of Pop, Michael Jackson, and some interesting advice Paul gave him. Check it out…
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2005-12-28 - 00:10:00
The New World Review
By Joe Lozito
Brave "New World"
I've made no secret of the fact that I'm not a huge Terrence Malick fan. I know I'm not making any new fans by saying that but I have to be honest here. There are some film aficionados who swear by the writer-director's less than prodigious output (four films in as many decades) but I'm not one of them. I've found Mr. Malick's work, from 1973's oft-copied "Badlands" to his pinnacle of ponderousness 1998's
"The Thin Red Line"
, to be overly self-conscious and preachy.
But with "The New World", Mr. Malick's envisioning of the story of Pocahontas, it seems as though everything I've held against Mr. Malick's previous efforts falls into place. The director's love of voice-overs, for example, helps inform the largely wordless love story between Captain John Smith (Colin Farrell, in his best role since…well…ever) and Pocahontas (remarkable newcomer Q'Orianka Kilcher). Mr. Malick also finds a perfect output for his fascination with nature. Nature is always a character in Mr. Malick's films. Here, the forests of Virginia are a perfectly unspoiled paradise.
"New World" is more of a visual poem than any film in recent memory. It's almost impossible to imagine how this film, which Mr. Malick also wrote, started on the printed page. Mr. Malick is such an astute visual storyteller that the film seems at once languid and brisk. Mr. Malick shoots the film largely in wide and medium shots, nearly doing away with close-ups, because so much of the story is happening around the characters, in the forest and wilderness behind them. "New World" contains none of the preachiness that plagued his
"The Thin Red Line"
. Instead, for a film that runs well into the two-plus hour range, "New World" contains precious little dialogue.
As far as the casting of Mr. Farrell goes, he no longer seems like the out of place modern actor, as Brad Pitt did in
or Mr. Farrell himself did in
. I don't remember when the Farrell hype started. Perhaps around 2000's "Tigerland", but certainly by
"Minority Report"
. Regardless, at some point Mr. Farrell was promised as the new leading man. "New World" may not cement that status but it certainly proves the actor's charisma. Like Russell Crowe, Mr. Farrell's hyper-macho off-screen persona serves him well in the role of worldly-wise Capt. John Smith. The fact that his relationship with Pocahontas comes across as sweet and true is a real accomplishment.
Not enough can be said about the wonderful Ms. Kilcher. Only 14 years old when the film was shot, her Pocahontas is the true spine of the film. Over the course of "New World" she visibly ages from an innocent nature girl to a world-weary adult. Ms. Kilcher embodies the spirit of Mr. Malick's elegiac film, nature inevitably corrupted.
"New World" is both a history and a fantasy. It's an imagining of the meeting between English settlers and the "Naturals", as the Native Americans were called. Under Mr. Malick's sure-footed direction, it's also a meditation on love, truth and family. And most importantly, it's the Terrence Malick masterpiece I, for one, have been waiting for.
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At once a history and a fantasy, Terrence Malick's masterful rendition of the life of Pocahontas is a visual poem and the finest film of his career.
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Iowa State University Extension and Outreach will host meetings in Madrid on Feb. 28 and Dubuque on March 6 to address emerging opportunities related to stover harvesting for the biomass feedstock needs of local industries.
About 70 percent of farmers report using at least one technology that provides them with Internet access, according to the 2012 Iowa Farm and Rural Life Poll. In addition, a basic cell phone was the most common communications technology used by farmers in the survey.
Iowa pork producers are invited to learn more about herd health and disease diagnostics, get livestock and grain economic outlooks, and hear about changing feed and diet options at the 2013 Iowa Pork Regional Conferences scheduled for February.
Although Iowa cattle typically can tolerate winter conditions surprisingly well, colder temperatures can mean higher nutrition needs for cow herds, says Iowa State University Extension beef specialist.
A roundtable session for beef feedlot operators will be conducted jointly by ISU Extension and Outreach and University of Nebraska Extension on Thursday, Feb. 21 from 12:45 – 3:45 p.m. Six Iowa locations will host the webinar sessions.
David Okerlund and a top-notch slate of dairy industry experts will focus on sustainability and industry perspective topics at the eighth annual I-29 Dairy Conference. The 2013 I-29 Dairy Conference will be held Feb. 27 and 28 at the Ramkota Inn in Sioux Falls, S.D.
Beef producers can get their fill of new beef technologies and information, followed by Iowa State University men's basketball at the third "Beef and Basketball" event in Ames on Feb. 23.
A two-day short course, Soil Fertility and Nutrient Management, will be held Feb. 13-14 at the Scheman Building on the Iowa State University campus in Ames. The ISU Extension and Outreach short course will focus on principles of soils, soil fertility and nutrient management.
Farm women can learn how to plan a successful farm transition through a five-session course offered by Iowa State University Extension and Outreach. The "Managing for Today and Tomorrow" program, a new Annie's Project course, is being offered in Jefferson on Thursday evenings, Feb. 21 – March 21.
Many farmers appear to believe that farmland is overvalued and eventually the market bubble will burst, according to the 2012 Iowa Farm and Rural Life Poll.
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Buenos Aires, Argentina
Last login about 1 month ago
Join Couchsurfing to see Kendra's full profile. It's free!View Full Profile
Shrink the world, connect to people from all over, make CS a way of life!
I lived in San Francisco for 7 years and just moved to Oakland about a year ago. I am from Southern California, and arrived here after living in Washington DC and London, and brief stints in South America, mostly Bolivia. I studied parasites and I like the weirdness of biology. I get pretty excited when talking about a subject that interests me, and I like hearing and telling great stories. I radically changed my life 2 years ago after reading a book called Sacred Economics, by Charles Eisenstein. I am now the co-founder of Bay Bucks, a local currency system in the SF Bay Area.
I love living in the Bay Area because I love the people I have met here, the things you can find, and the way you can be whatever you want. I love to dance (salsa, bhangra, charleston, whatever), to grow things, to learn from people, and to hear good ideas.
I like to meet and host people that are free-spirited, not afraid of new places or ideas, and bring the right energy and attitude.
My personal philosophy. Wow, that's intense for an online profile. But I think it's important, so... I love deeply and trust intuitively. I hate that money dictates so much of what people do. I try to see the amazingness of everything and the beauty of the world at all times. I don't like letting other people down. I hope to live simply, happily, and to be a lifelong learner.
Hosting, meet fellow CSers, meetings, parties, you name it...
Well.. I hosted a lot in SF, met other local hosters and their guests, attended meet-ups/activities... plan to do more of the same and eventually travel again when the opportunity presents itself. My favorite CS memory is the 2008 elections when I was hosting a Brit and a French guy who got to join in the wild street celebrations that night in SF, they had no idea it was going to be so crazy!
Local currency, permaculture, ecovillages, co-housing, death, mind-expanding activities, public health, dancing (especially salsa and other latin dances, bhangra, Charleston, hip-hop), food (especially locally farmed), ecology, jungles, insects, international goings-on...you know, frankly, almost everything interests me. You just have to be a good story teller. :)
This section is too overwhelming. I like rock n' roll, bluegrass, country, folk.... a bunch of bands that are totally diverse. My favorite authors are Charles Eisenstein, Tom Robbins, Dave Eggers, Philip Roth and I enjoy books about science (fiction and non), other cultures, and philosophy. I am in a book club and read all sorts of stuff I wouldnt normally choose for myself, and end up liking much of it. I love musicals and stage performances as well.
Seen many things, usually unexpectedly...Seen a saints day festival in rural Bolivia in the rain. The Bolivian desert, the Peruvian rivers, the Costa Rican and Bolivian jungles...it's all amazing. Beautiful beaches in New Zealand, Hawaii, even good old SoCal.
I can teach you about local currency systems, parasites, STDs and other health topics, maybe some basic gardening and permaculture. Also, English and Spanish language. Would like to learn: more languages, history of places I know little about (which is almost everywhere sadly, my history is really lacking), and probably a whole lot of other things I havent thought of. Would like to learn to crochet or knit, and sew better. Would like to learn about the flora and fauna of the places I go, and more permaculture.
Argentina, Belgium, Bolivia, Brazil, Chile, Colombia, Costa Rica, Ecuador, France, Germany, Lebanon, Mexico, New Zealand, Panama, Peru, Spain, Turkey, United Kingdom, Venezuela
United Kingdom, United States
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The Message audio Bible is now available on Bible Gateway! Click to learn more.
7:15 sheep's clothing . . . ravenous wolves. The message of false prophets may be attractive and even seem orthodox. The only way to know for sure is to allow time to see "their fruits" (vv. 16–20). Some of the false prophets' fruits are mentioned in the New Testament: controversies (1 Tim. 1:3), divisions (1 Tim. 6:3, 4), destruction of faith (2 Tim. 2:18), and self-destruction by heresy (2 Pet. 2:1).


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Master Certificate
Orchestration for Film and TV
Master Certificate8 Courses (24 Credits)
Full Price Tuition Pay All at Once & Save 10%$11,592.00 $10,432.80
Per Course / Per Term$1,449
Enroll in this Certificate
The ability to write beautiful music is rare, and rarer still is the ability to arrange that music in such a way that it enhances accompanying visual media, be it a film, television program, or video game. Drawing on the most up-to-date tools and information, this extensive certificate program will help equip you to become a more marketable composer and/or songwriter by offering in-depth instruction in orchestration while also delving into the placement techniques that will help your music find a home--and a paycheck--via TV, movies, video games, and other media.
8 Courses to Complete this Certificate
5 Required Courses
Essential learning for anyone interested in arranging music for a band, Arranging 1: Rhythm Section explores all aspects of writing and arranging for the rhythm section.
Explore the techniques of writing music that will appeal specifically to music supervisors, editors, directors, and producers across any number of different genres.
Learn to write and apply traditional orchestration techniques to both sampled performances and live orchestral performances.Log in or Sign Up to Sample This Course
Learn advanced orchestration strategies and approaches to writing for full orchestra, including both a live orchestra and sampled MIDI mockups.
Create original music to accompany a visual medium by learning fundamental to more advanced film scoring techniques.Log in or Sign Up to Sample This Course
Plus, Choose Any 3 Electives from Our Course Catalog
Suggested Electives
Learn to create your own original grooves by analyzing, writing, sequencing and recording the rhythms and styles that have influenced western contemporary music.
Gain a practical, real-world understanding of the sound and personality of woodwind and string instruments, and learn how to properly apply them to songs, arrangements, and compositions.
Learn to write music in the style of big budget Hollywood films and TV programs. Analyze melody, harmony, counterpoint, tempo, rhythm, and orchestration in a variety of genres to gain a complete recipe book for writing for film and TV.
Create great-looking music quickly and easily with the powerful Finale music notation software, and learn techniques to maximize speed, control, and accuracy.
Develop your writing and arranging skills for smaller bands and larger ensembles and learn techniques that can be applied to both live instrumentation or sequenced/sampled sounds.
Learn to create lead sheets, choral and instrumental scores, drum maps and guitar notation, and explore many other ways to use Sibelius for your own personal and professional needs.
Take your arranging abilities to the next level of development by studying more advanced techniques for voicing chords, orchestration, articulations, and background lines.
Gain a solid foundation of sound production and engineering skills that will prepare you to work at a game development company or as a freelance game audio professional.
Got a question? Contact our Academic Advisors by phone at 1-866-BERKLEE (U.S.), 1-617-747-2146 (INT'L), or by email at email@example.com. We can also answer basic questions in the comments below. Please note that all comments are public.
Fall Term Starts September 28 for Courses and Multi-Course Certificates
Create an Account
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Advisors on the Value of Getting Berklee Certified
Upon Completion of this Certificate, Students Receive:
Degree Path Certificates
What is a Degree Path Certificate?
Unlike our traditional multi-course certificate programs, all credits earned in a degree path certificate transfer directly into the certificate's correlating degree major.
Students who successfully complete a degree path certificate with a 2.7 GPA or higher are provisionally accepted into the certificate's correlating degree major in the online Bachelor of Professional Studies program, pending the student's completion of a degree application and application review by Berklee Online's Dean of Continuing Education.
Who are Degree Path Certificates best suited for?
Degree path certificates are best suited for students who aren't yet ready to pursue a robust online degree program, but who would like to begin completing credits that will transfer into Berklee Online's degree program in the future.
Can I enroll in a Degree Path Certificate even if I am not interested in pursuing an online degree?
Yes. All students are eligible to enroll in a degree path certificate, regardless of whether or not they plan to continue into a degree program upon completion of the certificate.
Can I receive federal financial aid for a Degree Path Certificate?
No, federal financial aid is not available for certificate programs.
I just completed a Degree Path Certificate and am interested in pursuing an online Bachelor of Professional Studies degree at Berklee Online. What do I do next?
When you are ready to enter the online Bachelor of Professional Studies degree program, complete an online degree application. In your application, be sure to select the major that corresponds with the certificate you completed. If you have any questions about applying, please contact an Academic Advisor at 1-866-BERKLEE (U.S.), 1-617-747-2146 (INT'L), or email@example.com.


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High School Daze
Inspired by true high school stories!
The Little Buzzers
A cute cartoon, inspired by unadulterated rage and hatred.
Socially Awkward Male Virgins!
Great game!
I played this game and it was so awesome that this was the most greatest game in the world!
^_^ i love it man simple yet fun and interesting
cool strwbarry's voting power never fail's thx to his mini cannon car lol nifty little game man really fun ^_^
This is an awesome game! Vote 5 for it and rate it 10!
Happy Early Clock Day!
How fortunate and interesting you would be to have this featured on none other than the day before the next Clock Day! I had tons of fun playing this mostly because the graphics are so good. This definitley defies some of the more spammy flash that people put up on Clock Day. I love the goofy sounds, particulary with how the jeep bounced up and down. I love all the bright colors used in this and the goofy sounds you make when you upgrade something. While not the best control, definitley something great.
Cool Clock Day tribute. This is really how I visual Newgrounds on Clock Day: people driving in cars and voting 5 on everything. The game is good and it's fun


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Yokkaichi City Hotel
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TripAdvisor Reviews Yokkaichi City Hotel
Travel Blogs from Yokkaichi
Day 7
... check in, just time to dump our bags & off we went for a walk around the town we went to a museum, a shrine, the Takayama festival float exhibition hall, we then went to the old part of town. We had a beautiful tea not far from there. When we got back from tea we had another spa, getting used to it (in the nude) still lots of laughs. It's now 9.00 and ready for bed. Ran out of battery so no pictures of ...
It was Good but it was Weird
... into the weather (in a car this time!) to go to a nice restaurant. Luke told us this would be an 'experience dinner.' The dinner was in multiple courses and we got two different types so we could all share the food to try everything. We ate through maybe 8 different sets of dishes with everything from sushi to soup to dessert. Luke ordered us a special roll to top off the meal - he quietly warned me to just hang back and watch the boys eat it. The laughing staff tipped us ...
The bus ride from Takayama was very scenic. Still lots of snow on the ground as we crossed parts of the Alps. We arrived in Nagoya mid afternoon and walked to the hotel, the Nagoya Crown Hotel. Its ok, nothing special, but has a natural hot spring bathes in the basement. Maybe Shauna will use it. As its a blue sky day and quite warm we start walking exploring the city. Nowhere near as big or busy as Tokyo, and from what we have seen so far, its pretty nice.
8th, ...
Tsuzuki to Nagoya day trip
... 333;.[citation ...
Our way to Nagoya
Finally in Japan, we're met by Joe's parents
s o
Nagoya (名古屋市 Nagoya-shi


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A ground-breaking new production of the beloved musical performed simultaneously in Spoken English and American Sign Language (ASL).
285 backers pledged $30,706 to help bring this project to life.
And so it begins once again!
The Spring Awakening gang is back together at the Wallis Annenberg Center for Performing Arts in Beverly Hills, rehearsing as we speak. But it's not the same show by all... Read more
A new year. And a new life for Spring Awakening.
With your help last summer, we were able to stage "Spring Awakening".
As you probably know, the show succeeded beyond our wildest dreams. The show was heralded as an "emotional... Read more
Successfully raised $30,707 USD with 285 backers
The last few hours
You guys have been amazing and we are sincerely thankful for your commitment to our cause thus far. With just about 5 hours to go we are on the last... Read more
We have been touched.
Today, we met our initial goal of $25,000!
Thank you so much for the outpouring of support, which will make this amazing version of Spring Awakeningpossible! Pledges came in... Read more
Project launched


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5 Heart-Healthy Tips for Lean Living!
…these substances give you a boost or some relaxation, but in the long run, they are detrimental to your physical well-being. Better yet, toss all coffee including decaffeinated and substitute green tea. The nutrients in green tea will help you burn more calories at rest. Now it's your turn: Do you…Read More


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GM to Hold Groundbreaking Ceremony for New Paint Shop in Flint
GM is set to break ground Monday on a massive new paint shop at its Flint Assembly location.
GM is set to break ground Monday on a massive new paint shop at its Flint Assembly location.
Has your vehicle been damaged due to potholes? Know of a BIG pothole. Here's how to report both.
The bus hit at least three light poles,four trees and a building before it stopped.
We're not the only ones who have problems on the slippery roads. Even the pros do.
"So you're saying there's a chance?" The Michigan Department of Transportation has outlined how to file claims for cars damaged by potholes.
The video is devastating. Nature gobbled up some of the fastest -- and coolest -- cars to ever roll off a GM assembly line.
A video was taken by a woman traveling in the opposite direction. Warning! Video Is very graphic.
Driving into work at four am is always a bit more challenging in the dark. I thought I would snap a few photos through the windshield on my way in this morning.
It all started to happen yesterday morning at around 8:45am.
For the second time this month, the Flint-built Chevy Silverado is making news and for good reason!
An Ingham County sheriff's deputy vehicle's dash cam caught this little video piece.
Unfortunately, it's that time of year again! Pothole season has begun in Michigan. Here's how to report them!


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routes du bonheur Suggestions for itineraries to discover the world
Restaurant in town. Japan,Tokyo
Menus 15000 JPY t. 8% s. 20% (lunch) - 25000 JPY t. 8% s. 20% (dinner)
Lift / Elevator
Air-conditioned restaurant
Open all year
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Paul Simon :: 04.27.11 :: The Fillmore :: San Francisco, CA
Paul Simon is not a big guy. I knew this before walking into The Fillmore but the initial sight of him as the lights dimmed and he joined his band was striking. To look at him he's not the kind of dude that commands the attention of a boisterous throng, but Simon wielded a forceful, guiding hand on the room, capturing all but a few pockets of numbnuts chatting about their workday or Facebook postings while he plied his craft. Given that the man has commanded the attention of a Central Park sized mob it shouldn't have come as any surprise how masterfully he worked The Fillmore, but the force and authority of this performance were something to behold – a master and his masterful compatriots in complete control of every aspect of an emotional, expert performance that ranged thoughtfully through an amazing catalogue.
A smile bomb went off as the opening bars of "The Boy In The Bubble" kicked off the night. Always less of a Graceland zealot than most, I was however struck by how modern the song still sounds, as if we've finally caught up with what Simon was laying down in 1986. The intercontinental drift of his Tin Pan Alley/Greenwich Village certified style has been present since the days his named was hitched to Art Garfunkel, but his deep reach into American musical traditions and their kindred vibrations elsewhere seems downright prescient now. Throughout this evening, as snippets of New Orleans second line, Nigerian funk, Madagascar twang or whatnot bubbled up, one felt the man's brilliance and vision in music that genuinely bridges gaps, and maybe even makes us better people if we bother to wrestle with the complexities inside his songs.
Surrounded by utter pros, Simon stretched out his arms a few times and looked like he was ready to take wing. Beautiful to see a veteran so in the moment, so charged up by the packed masses journeying along with the folks onstage. There was a pretty thick connection flowing back and forth between the conductors and the travelers, perhaps a shared comprehension that this music contains the kernels of understanding and joy. In Simon's worldview, we are reflected in our dinged-up glory and tattered perseverance, a real vision brought forth by Simon's humor and honesty.
For some reason, this all seemed evident – as if glowing on the surface of everything around me – in the relatively intimate confines of The Fillmore, which has many times served as a crucible for intense, even life-altering moments. Where one might normally expect to see an artist like Paul Simon with tens of thousands, the 900-1000 folks shoulder-to-shoulder in SF were gifted with a close-up view of one of the greatest musicians America has produced in the past 100 years. One felt both the sharpness of his insight and his abiding compassion in the careful weaving of tunes past and present, in the hearty, jovial interplay between the musicians onstage, and ultimately in the intangible vibe permeating the room, a shiningly smudged patina that left the building with us at evening's close.
Ain't it strange the way we're ignorant
How we seek out bad advice
How we jigger it and figure it
Mistaking value for the price
And play a game with time and love
Like a pair of rolling dice
So beautiful
So beautiful
So beautiful
The Boy In the Bubble, Dazzling Blue, 50 Ways To Leave Your Lover, So Beautiful Or So What, Vietnam (Jimmy Cliff cover), Mother And Child Reunion, That Was Your Mother, Hearts And Bones, Mystery Train, Wheels (Chet Atkins cover), Slip Slidin' Away, Rewrite, Peace Like a River, The Obvious Child, Only Living Boy In New York, Getting Ready For Christmas Day, Love Is Eternal Sacred Light, Father And Daughter, Diamonds On the Soles Of Her Shoes, Gumboots
Encore 1: The Sound Of Silence, Kodachrome, Gone At Last, Here Comes the Sun (Beatles cover), Late In the Evening, Proof
Encore 2: Still Crazy After All These Years
Paul Simon Tour Dates :: Paul Simon News
JamBase | San Francisco
Go See Live Music!
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