Human Tracking by Particle Filtering Using Full 3D Model of Both Target and Environment

This work presents a new approach based on particle filtering to directly estimate the 3D positions of humans. Our system can predict occlusions due to other movements because we track humans in a 3D space, not on a 2D image plane. In addition, we introduce a 3D environmental model as the background model for tracking. This makes it easier to handle occlusions due to fixed objects in the environment. The 3D environmental model is automatically constructed by our original method from video sequences. Experiments show that our system is stable under occlusions due to the movements of both other subjects and fixed objects