Active Head Tracking Using Integrated Contour and Template Matching in Indoor Cluttered Environment

Abstract

Due to the fact that existing surveillance systems usually employ fixed or automatically-patrolled cameras, they cannot effectively track invaders in real-time. Therefore, an automatic head tracking system in indoor cluttered environment is proposed. This system consists of two parts, automatic head tracking system and remote monitoring and control system. In the automatic head tracking system, the position of human head on image plane can be determined based on head tracking strategy. According to the position and size of human head on image plane, a suitable fuzzy rule is designed to maintain the position of human head near image center with appropriate size by controlling the active camera via pan, tilt, and zoom. Specifically, the position of the moving object on image plane can be determined using moving object detection method. Then a sizable tracking window to track human head is used to reduce redundant computation. Moreover, color recognition, template matching, and head contour matching methods are integrated for tracking human head robustly. In order to achieve better performance, Kalman filtering is employed to predict the position of human head on image plane. The proposed active head tracking system has been successfully validated in indoor cluttered environment.