title: Real Time Camera/Image Based Large-Scale Slam Algorithm
body: <p>I want to use an already implemented <strong>SLAM algorithm</strong> for <strong>mapping my college campus</strong>.</p>
  
  <p>I have found some algorithms <a href="https://openslam.org/" rel="nofollow">on OpenSLAM.org</a> and some other independent ones such as <a href="https://vision.in.tum.de/research/vslam/lsdslam?redirect=1" rel="nofollow">LSD-SLAM</a> and <a href="http://wiki.ros.org/hector_slam" rel="nofollow">Hector SLAM</a>, which show some promises but they have limitation such as they use LIDAR, or don't extend to large dataset etc.</p>
  
  <p>SLAM has been an active topic for many years and some groups have also mapped an entire town. Can someone point me to such efficient algorithm?</p>
  
  <p>My requirements are:</p>
  
  <ol>
  <li>It <em>must</em> use RGB camera/cameras.</li>
  <li>Preferably produce (somewhat) dense map of area.</li>
  <li>It should be able to map large area (I have seen some algo which can only map up to a desk table or room, but they usually lose track if there is jerk in camera motion (Observed in LSD SLAM) or take very few landmarks which is only useful for study purposes).</li>
  <li>Preferably a ROS implementation.</li>
  </ol>