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Research on Human Motion Recognition Based on Video Sequences

Author: XiongJing
Tutor: LiuZhiJing
School: Xi'an University of Electronic Science and Technology
Course: Applied Computer Technology
Keywords: Intelligent Systems Behavior recognition Hidden Markov Models Convex hull algorithm
CLC: TP391.41
Type: Master's thesis
Year: 2008
Downloads: 399
Quote: 6
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Abstract


Dynamic on-site visual monitoring is an emerging application direction of the field of computer vision . Visual monitoring different from the traditional sense of the monitoring system in its intelligence . In short , not only with a video camera instead of the human eye , and replacing people with computers to help people , to accomplish the task of monitoring or control , so as to alleviate the burden of the people . This will not only be able to save a lot of manpower , material and financial resources , it is more important to be able to detect the condition to avoid the occurrence of the crime . The Visual Surveillance has broad application prospects and potential economic value . Attracted the attention of domestic and foreign research institutions and scholars in recent years . Moving target behavior recognition follow three basic steps of the moving target detection , tracking and behavior recognition . Moving target detection and tracking behavior recognition on the basis of this article briefly describes the method of target detection and tracking , focus on moving target behavior recognition algorithms . The article describes the first system image processing platform and used image processing methods , listed some of the common methods in the detection and tracking of moving targets , described the methods used in the system last brief comparison . Identify expand research focused on moving target behavior , a of Hu moment and hidden Markov model , through detailed analysis , found hidden Markov algorithm moving target behavior better judgment , but there are also some disadvantages for its a problem final convex hull algorithms to find the feature points , and hidden Markov model are combined , the original algorithm is improved , this improved algorithm has a good performance by the experimental results demonstrate .

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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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