EURASIP Journal on Advances in Signal Processing - Special title on vehicular ad hoc networks
Combining edge and color features for tracking partially occluded humans
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Directional eigentemplate learning for sparse template tracker
PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part II
Real-time face tracking and recognition by sparse eigentracker with associative mapping to 3D shape
Image and Vision Computing
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Multiple target tracking is a challenging problem, especially when targets are frequently crossing each other. It becomes very difficult and confusing when some targets are often occluded by other targets. This paper proposes a novel tracking method for the problem using an appearance-based condensation tracker. In order to overcome difficulties in the occlusion problem, a target object is regarded as a set of partsthat constrains each other in the target structure. While each part is tracked basically in the condensation method, all the parts cooperate in the drift step of the condensation. Experimental results show the effectiveness of the proposed method formultiple person tracking and human face tracking.