Dynamic visual tracking based on multiple feature matching and g–h filter
The area-based matching approach has been used extensively in many dynamic visual tracking systems to detect moving targets because it is computation efficient and does not require an object model. Unfortunately, area-based matching is sensitive to occlusion and illumination variation.
In order to improve the robustness of visual tracking, two image cues, i.e., target template and target contour, are used in the proposed visual tracking algorithm. In particular, the target contour is represented by the active contour model that is used in combination with the fast greedy
algorithm. However, to use the conventional active contour method, the initial contour needs to be provided manually. In order to facilitate the use of contour matching, a new approach that combines the adaptive background subtraction method with the border tracing technique was developed
and is used to automatically generate the initial contour. In addition, a g–h filter is added to the visual loop to deal with the latency problem of visual feedback so that the performance of dynamic visual tracking can be improved. Experimental results demonstrate the effectiveness
of the proposed approach.