Probabilistic Tracking of Objects with Adaptive Cue Fusion Mechanism

A tracking method based on adaptive multiple cue fusion mechanism was presented, where particle filter is used to integrate color and edge cues. The fusion mechanism assigns different weights to two cues according to their importance, thus improving the robustness and reliability of the tracking algorithm. Moreover, a multi-part color model is also invoked to deal with the confliction among similar objects. The experimental results on two real image sequences show the tracking algorithm with adaptive fusion mechanism performs well in the presence of complex scenarios such as head rotation, scale change and multiple person occlusions.