People counting based on skeleton feature
Xia Jingjin · Journal of Computer Applications · 2014
Concerning the problem that pedestrians would be partially or seriously shaded by each other in video monitoring,this paper proposed a people counting algorithm based on human body skeleton feature. At first,the initial human skeleton was extracted by morphological skeleton extraction algorithm. Then the optimal skeleton feature was obtained by eliminating outliers and pseudo branches. Finally,this paper established a head detection response rule through analyzing the characteristics of skeleton in head areas to detect the head of pedestrian,and completed people counting by counting the heads of pedestrians. The experimental results show that the algorithm can solve the problems of partial and serious shading in video monitoring. For relatively sparse scene,the overall people counting accuracy rate of the algorithm is about 95%.