Robust Visual Tracking in Cluttered Environment Using an Active Contour Method

This study develops a highly reliable real-time visual tracking system capable of tracking a moving target in cluttered environment. The proposed system architecture can be divided into three main parts - the target detector, the target information extractor and the target tracker. The first part detects any moving object in the image, using the moving edges technique. Next, by integrating the information from the target detector and the attractable snake model, the second part automatically extracts the target's contour, illumination and color information to enable the target to be tracked. Finally, by adopting a new hybrid matching method, the third part enables the system to continuously track the target with great robustness and adaptability. Notably, this hybrid matching method incorporates the template matching method with a modified contour matching method. Furthermore, the visual tracking system developed in this study is established on a low-cost commercial camera platform, which can be controlled by a personal computer through an RS232 serial port. Finally, several experiments, including object tracking and human head tracking, are conducted to verify the robustness of the tracking system.