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Research and Implementation based on weighted HU invariant moments surveillance video of human behavior recognition method

Author: ZhangLin
Tutor: ZhouMingQuan
School: Northwestern University
Course: Computer technology
Keywords: Intelligent Monitoring Moving Target Detection Hu Moment Invariants Hidden Markov Model
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 43
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Abstract


With the extensive use of video surveillance systems in Community security, safety and other aspects, How to achieve rapid,accurate detection of abnormal behavior become video monitoring a problem to be solved, but also become a hot research topic in the field of computer vision. This paper study and improved the movement Human behavior in the processing of identification key algorithms, mainly including work progress:(1)As to the image blurring rough for monitoring, before graphic image processing, we choose the methods of smoothing, filtering and other pre-processing, and then the image has not been destroyed.(2)In moving target detection, change the background image for the inconsistency, while ensuring the efficient simplicity, this paper presents a simple change in the background of the case that the problem of the shadow, and select updating and threshold selection combined to improve performance of the algorithm based on adaptive background; in the context of complex situations, we choose the Gaussian mixture model-based extraction of moving targets, through the analysis of test results, we improve the Gaussian mixture model parameters, and solve the light and the trees outside disturbances such as the impact of changes. Finally, a fast YUV color space shadow suppression algorithm.(3) In identifying the target behavior in the campaign, in order to make the efficiency for identifying abnormal behavior more convenient, we improve the weighted Hu invariant moments as the target, the use of sliding window mechanism to match the results of successive video frames a comprehensive analysis to human behavior identification; while the target contour based features and hidden Markov model-based algorithm for the minimum bounding rectangle of the target aspect ratio, target coverage and target contour feature vector consisting of features described as characteristic of human behavior, the human behavior on the basis of discrimination is abnormal.This design implements a video surveillance system of motion human identification. we show that:the proposed method can effectively detect moving targets in real-time video and identify the movement of human behavior.

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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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