Study On Rigid Moving Target Tracking Algorithm

Moving target tracking plays an important role in military visual missile guidance, robot vision navigation, industrial product inspection, medical diagnosing and traffic surveillance, etc. Due to the facts of variety of the feature of the targets, the complexity of the environmental background, moving target tracking is a challenging subject. Especially the occlusion problem in the course of tracking has been one of the crucial restrictive factors to the robustness of the tracking algorithms.This thesis mainly focuses on the tracking of rigid moving targets. It detailedly discussed the tracking algorithm based on edge-feature-matching, particle filter and intensity-correlation-matching algorithms under occlusion.The major contribution can be summarized as follows:1. The contour line or the border line of the rigid target is the important clue and feature for visual sense. Two consecutive frames subtraction is applied to detecting the moving objects and random edge feature is contributed to object tracking. The algorithm can adapt well to the disadvantageous factors such as angles of target point, rays, and moving states of targets.2. Aiming at the general tracking of rigid targets under occlusion, we proposed a tracking algorithm based on edge and intensity matching. Edge matching algorithm is applied when the intensity of target is uniform, while intensity matching algorithm is applied when the intensity information is abundant. The target is adaptively divided in order to make each block with distinct feature to increase the accuracy degree of occlusion estimating and block matching. Then through blocks, the occlusion regions are accurately estimated, and match and vote are made using the remaining un-occluded blocks. Kalman prediction is used to track when full occlusion happens. This algorithm can track rigid target accurately and real-time.