Person and Vehicle Tracking in Surveillance Video

This evaluation for person and vehicle tracking in surveillance presented some new challenges. The dataset was large and very high-quality, but with difficult scene properties involving illumination changes, unusual lighting conditions, and complicated occlusion of objects. Since this is a well-researched scenario [1], our submission was based primarily on our existing projects for automated object detection and tracking in surveillance. We also added several new features that are practical improvements for handling the difficulties of this dataset.

[1]  Mubarak Shah,et al.  A noniterative greedy algorithm for multiframe point correspondence , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Mubarak Shah,et al.  Automatically Tuning Background Subtraction Parameters using Particle Swarm Optimization , 2007, 2007 IEEE International Conference on Multimedia and Expo.

[3]  Yaser Sheikh,et al.  Bayesian modeling of dynamic scenes for object detection , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Mubarak Shah,et al.  A hierarchical approach to robust background subtraction using color and gradient information , 2002, Workshop on Motion and Video Computing, 2002. Proceedings..

[5]  Mubarak Shah,et al.  Tracking and Object Classification for Automated Surveillance , 2002, ECCV.