Detecting individual in crowd with moving feature's structure consistency

Yuanhao Yu, Zhen Lei, Dong Yi, Stan Z. Li

Abstract: In this paper, we present a method for detecting individuals in crowd by clustering a group of feature points belonging to the same person. In our approach, a feature point is considered to contain three attributes: the motion trajectory in video sequence, the sparse local appearance around point in current frame, and the structure relationship with body center related with local appearance. We exploit these attributes to cluster them appearing on the same individual to achieve detection purpose. The algorithm does not require observing entire human body and could discriminate different individuals under overlap. Our experiments show that this approach advances the performance of detecting individuals in crowds.