COMBINATION OF SIMPLE VISION MODULES FOR ROBUST REAL-TIME MOTION TRACKING

In this paper we describe a real time object tracking system consisting of three modules (motion detection, object tracking, robot control), each working with a moderate accuracy, implemented in parallel on a workstation cluster, and therefore operating fast without any specialized hardware. The robustness and quality of the system is achieved by a combination of these vision modules with an additional attention module which recognizes errors during the tracking. For object tracking in image sequences we apply the method of active contour models (snakes) which can be used for contour description and extraction as well. We show how the snake is initialized automatically by the motion detection module, explain the tracking module, and demonstrate the detection of errors during the tracking by the attention module. Experiments show that this approach allows a robust real-time object tracking over long image sequences. Using a formal error measurement presented in this paper it will be shown that the moving object is in the center of the image in 90 percent of all images.