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The Research on Tracking Algorithms of Moving Targets in Video Images

Author: BaoYuGang
Tutor: ZhaoChunZuo
School: Harbin Engineering University
Course: Communication and Information System
Keywords: Target tracking Mean Shift Algorithm Camshift algorithm Particle filter
CLC: TP391.41
Type: Master's thesis
Year: 2010
Downloads: 383
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Abstract


Moving target tracking in video images is an important research topic related to the development of digital video technology , video image processing , video surveillance , medical image analysis , biology , automatic control , computer image processing , artificial intelligence, and many other areas , has important theoretical value and practical significance . The method of moving target detection and tracking in-depth research , the classic algorithm improving key work in the following areas : First , target detection method is mainly to study the inter-frame difference method based on hierarchical block background model to estimate the background subtraction , and put forward the continuous frame difference method and background subtraction method to achieve the moving target detection , the method can be good enough to avoid the continuous frame difference method for the two images overlapping objectives can not be detected out background subtraction easily influenced by the external environment . Secondly, the use of a very wide range of Mean Shift algorithm based on the current track the target process is prone to tracking area offset , as well as tracking failed with increasing cumulative error , the classification block background model to estimate the background phase the subtraction with traditional Mean Shift algorithm combined with target tracking method , the improved method can well suppress the tracking area offset as well as the track failed error accumulation , this algorithm has better robustness . Again , the target area for traditional Camshift algorithm requires manual selection, and tracking failed when a color similar to the background color of the target , the the KIM method and Camshift algorithm combined target tracking algorithm , the method can be a good determining the moving target area, especially for the partial occlusion target when it is not blocked , the method can be more complete to extract the outline of the moving target . Accurately track to achieve the target . Finally, the article on the basis of the study particle filter tracking method for use of a single feature on the target track is prone to the case of tracking failure , color information and shape information combination to achieve a description of the target feature , and the feature is applied to the particle filter tracking method , this method has good adaptability to the short-term goal blocked .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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