Particle Filter Based on Multiple Cues Fusion for Pedestrian Tracking
A pedestrian tracking algorithm is proposed in this paper which combines color and edge features in particle filter framework to resolve the pedestrian tracking problem in the video set. The color feature tracking work well when the object has low object deformation, scale variation and some rotation, while the edge feature is robust to the target with similar color to its background. In the paper, color histogram (HC) and four direction features (FDF) of the tracking objects is utilized, and experiments demonstrate that pedestrian tracking with multiple features fusion have a good performance even when objects are occluded by other human bodies, shelters or have low discrimination to background.
Keywordsparticle filter tracking color histogram four direction features
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