Research On Moving Target Tracking Technology

Target tracking and recognition as a core computer vision research, a growing number of algorithms have sprung up. According to the difference of the target tracking and scene, tracking algorithm is not the same taken, which requires the design stage in the algorithm can take into account the various characteristics of a variety of possible targets to be tracked and the scene. In this paper, target tracking, updating and occlusion handling templates for different algorithms are compared. Occlusion is an issue in the tracking field, how to handle occlusion is a key measure of tracking algorithm for robustness. This article, on the issue, proposed a new algorithm of handling occlusion fragments-based tracking. When the target happened partial occlusion or pose change, the strength of the remaining effective patch of information remains credible. Algorithm uses the Bhattacharyya coefficient of similarity measure as a candidate target piece with the corresponding template piece to track target effectively. Using H back projection method to distinguish between occlusion and pose change. According to the different types of occlusion, it makes the appropriate handle to realize robust tracking the target. The present experiment proposed the concept of relevance occlusion and non-relevance occlusion, increasing the reliability of algorithm for tracking. Through fragments-based tracking, and taking into account the correlation between the target and obstructions, it will make improved about the Tracking efficiency significantly.