Hernan Badino Edit
https://www.youtube.com/watch?v=fqWdSfN9FiA 100 fps & Very Low Drift Visual Odometry - New College Data Set (source code available) http://lelaps.de/projects.html The video shows the results of estimating visual odometry and independent motion on the New College data set (http://www.robots.ox.ac.uk/NewCollegeData/). Visual odometry is obtained by the algorithm of Badino and Kanade  that minimizes the reprojection error of tracked features. Features are tracked by the KLT algorithm. Independent motion is obtained by tracking feature position and velocity over time by means of a Kalman filter.
Main window: the arrows show the prediction of position of the tracked features in 2 seconds. Color encodes the 3D Euclidean speed from green to red. Top-right: optical flow vectors of the tracked features. The color encodes the length of the optical flow vector. Middle-right: color encoded stereo disparities from green to red. Bottom-right: estimated traveled path by dead-reckoning (no loop closure) The source code is available on SourceForge.net: http://sourceforge.net/projects/qcv/
 Hernan Badino and Takeo Kanade. A Head-Wearable Short-Baseline Stereo System for the Simultaneous Estimation of Structure and Motion. In IAPR Conference on Machine Vision Applications (MVA), Nara, Japan, June 2011.