ACCELERATED PEOPLE TRACKING USING TEXTURE IN A CAMERA NETWORK
Wasit Limprasert, Andrew Michael Wallace, Greg Michaelson · 2012
We present an approach to tracking multiple human subjects within a camera network. A particle filter framework is used in which we combine foreground-background subtraction with a novel approach to texture learning and likelihood computation based on an ellipsoid model. As there are inevitable problems with multiple subjects due to occlusion and crossing, we include a robust method to suppress distraction between subjects. To achieve real-time performance, we have also developed our code on a graphics processing unit to achieve a 10-fold reduction in processing time with an approximate frame rate of 10 frames per second. 1