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Detection method of moving object under dynamic scene

A technology for moving objects and detection methods, applied in the field of video processing, can solve the problems of repeated calculation and information redundancy, and achieve the effect of saving storage space, realizing simple and effective, and avoiding repeated calculation.

Inactive Publication Date: 2005-01-12
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to provide a method for detecting moving objects in a dynamic scene in view of the deficiencies of the above-mentioned technologies and the actual needs of the video surveillance system, which does not need to assume the distribution form of the background in advance, and avoids information redundancy and Repeated calculations, the established non-parametric multi-modal model of diverse samples can handle complex scenes and incomplete static situations, laying a solid technical foundation for higher-level video analysis systems such as tracking and classification

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  • Detection method of moving object under dynamic scene
  • Detection method of moving object under dynamic scene
  • Detection method of moving object under dynamic scene

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[0016] In order to better understand the technical solution of the present invention, further detailed description will be made below in conjunction with the accompanying drawings and embodiments.

[0017] figure 1 It is a block flow diagram of the method of the present invention. In order to establish a dynamic background model for moving object detection, N frames of continuous image sequences are required as samples for model training. For a certain pixel (x, y), it is necessary to extract new diversity samples (M x，y ), and at the same time get the window width σ x，y . Then the kernel density estimation is performed on the current frame image, and the estimation result is thresholded, and finally the moving object detection result is obtained. figure 2 yes figure 1 Flow chart of the extraction of diverse sample sets in . From the histogram of the original training sample, first obtain the gray value with the largest frequency of occurrence, and then select the gray ...

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Abstract

The method includes following steps: the kernel density estimation function is used to build a modeling for pixel process; the distribute free probability density is used to estimate the distribution of pixel gray scale of image calculated by theory. The method gets the sample set of time domain diversity from original training sequence to use it in modeling training. In the procedure of extracting background and testing moving objects, the storage and usage of original training data is not needed, that saves storage space and avoids multiple calculations.

Description

technical field [0001] The invention relates to a moving object detection method in a dynamic scene, which is mainly used for higher-level video analysis such as classification and tracking of moving objects in a video monitoring system, and belongs to the technical field of video processing. Background technique [0002] Moving object detection is a key issue in video analysis of systems such as video surveillance, human-computer interaction, and traffic monitoring. The results are usually used for higher-level analysis and processing such as target tracking and classification. The effectiveness and robustness of detection methods are critical to the entire video system. As an effective method of motion detection, the background subtraction method (Background Subtraction) subtracts the scene background from the current image to obtain the motion foreground, which has the advantages of accurate positioning and no expansion of the motion area. It is usually assumed that the ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/20G08G1/01H04N7/18
Inventor 毛燕芬施鹏飞
Owner SHANGHAI JIAO TONG UNIV
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