期刊名称：International Journal on Smart Sensing and Intelligent Systems
印刷版ISSN：1178-5608
出版年度：2015
卷号：8
期号：1
页码：181-198
出版社：Massey University
摘要：Moving target detection and tracking algorithm research content is very broad and complexapplications, without and different target features directly affects the detection of selected trackingalgorithm. So far still does not exist a universal algorithm for perfect can be suitable for variousapplications, so the detection and tracking of moving targets is still a valuable research subject of. Theresearch work in this paper is in the field, the moving target detection spatiotemporal correlation anddifference contour tracking algorithm based on a fixed background. The algorithm in the backgroundunder the condition of fixed to pay a smaller time complexity, the target detection and tracking has agood effect, so it has higher application value. Based on solving the detection and location of movingtarget tracking in real-time and accuracy requirements, a new moving target detection spatiotemporalcorrelation and difference contour tracking scheme based on the practical implementation, at the sametime analysis and the experimental results are given. In the moving target tracking, tracking method ismainly traditional correlation method target based on template matching. The matching process is timeconsuming, so the actual use of more of the improved algorithm of correlation method, the improvedalgorithm attempts to improve the efficiency of feature matching and search range, and also achieved acertain effect, the some excellent tracking algorithm. This paper presents an improved active contourmodel tracking algorithm, improve the tracking efficiency and quality, the algorithm first from theframe difference detection results to find the moving target coarse contour, and then the convergenceof coarse contour by using improved Snake algorithm, the right edge to get the target in the course ofthe campaign, in order to achieve the tracking of moving objects..
关键词：Moving object; detection; active; pattern recognition; image features
