Dynamic color tracking in clutter based on sampling
Xin Lu, Shunichiro Oe, Toshiyuki Kashiwagi, Tao Lu · 2004
Visual tracking could be treated as target state representation and target state inference problem in an image sequence. Moreover, in cluttered and dynamic environments the better probabilities of accurate tracking depend on richer representation and more robust inference. Target state representation could be considered as color segmentation, contour detection and position mark and target state inference could be treated as an evaluation from old states to new one in fuzzy logic at every step of an image sequence. This paper presents a special tracking system based on factored sampling model in order to resolve difficult and complicated visual tracking problem, such as a changing of target's representation, a clutter of environments and an interaction of target and camera. This tracking system is applied to changeful target tracking by handling the related information to sample-set between every two time-steps in an image sequence and implemented in real time system at around 20 Hz with 640*480 pixels image. Specially, color and position distribution of a target have been used in this system to estimate the target situation. The results show the robust, real-time system is able to track a target with enough accuracy and automatically control the camera's pan, tilt and zoom to remain the object centered in the field of vision.