A Contour-Based Moving Object Detection and Tracking

Abstract

We propose a fast and robust approach to the detection and tracking of moving objects. Our method is based on using lines computed by a gradient-based optical flow and an edge detector. While it is known among researchers that gradient-based optical flow and edges are well matched for accurate computation of velocity, not much attention is paid to creating systems for detecting and tracking objects using this feature. In our method, extracted edges by using optical flow and the edge detector are restored as lines, and background lines of the previous frame are subtracted. Contours of objects are obtained by using snakes to clustered lines. Detected objects are tracked, and each tracked object has a state for handling occlusion and interference. The experimental results on outdoor-scenes show fast and robust performance of our method. The computation time of our method is 0.089 s/frame on a 900 MHz processor.