Tracking People using Multiple Cameras
Computer Vision Central - Posted on December 27, 2011 at 11:48 pm.
Tracking multiple people from standard cameras is challenging, mostly due to the occlusions that occur as soon as several people are involved. We tackle this problem by using several cameras, observing the scene with different points of views. We developed a people detection algorithm called POM that uses a generative model of background subtraction to estimate the positions of people in an individual time frame.
Using this detection result, we then rely on global optimization methods, such as Linear Programming or more recently K-Shortest Path (KSP), to link together detections obtained at independent time frames.
The frame-independent people detector working together with a joint optimization method for tracking form a very robust system that allows to track people reliably instead of significant occlusions, while exhibiting real-time performance.