Robust human detecting and tracking using varying scale template matching
Songmin Jia, Shuang Wang, Lijia Wang, Xiuzhi Li · 2012
This paper employs the methods of human detecting and tracking based on stereo vision in the indoor environment. A novel method of template matching based on head-shoulder model is proposed to detect human. The presented method is achieved by attaining the disparity images from the stereo cameras, and extracting the head-shoulder model of human. Robust human tracking is performed using the EKF. The EKF is used to locate the position of the target and it is flexible and effective in the practical environment. When the human is occluded by other objects, the EKF is used in predicting the trend of human movement. This paper introduces the architecture of the proposed method and presents some experimental results.