Foreground detection method based on motion vector division

A technology of motion vector and foreground detection, applied in image analysis, image data processing, instruments, etc., can solve the problem of non-stationary scene sensitivity, achieve fast running speed, eliminate jitter and false detection

Active Publication Date: 2015-10-07
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

[0007] Wang Yongzhong, Liang Yan and others from Northwestern Polytechnical University are engaged in the research of target tracking. The main achievement: In view of the shortcomings of the traditional mixed Gaussian background modeling method that is sensitive to non-stationary scenes, a new mixed Gaussian model is proposed.

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  • Foreground detection method based on motion vector division

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Embodiment Construction

[0051] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0052] The invention provides a foreground detection method based on motion vector division. When distinguishing the motion trend of the foreground and the background, the dense optical flow is used as the basis for the distinction. For each frame of image in the video file, the Gaussian pyramid is used to decompose the image downward, and then the dense optical flow calculation method of Gunnar Farneback is used, and then the calculated optical flow field is quantized to obtain a discrete motion vector m...

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Abstract

The present invention provides a foreground detection method based on motion vector division, characterized in that discrete motion vectors are used for dividing a movement trend to perform foreground detection, when the movement trend of a foreground and the movement trend of a background are distinguished, dense optical flow is used as a distinguishing basis, quantitative processing is performed for a calculated optical flow field to obtain a discrete motion vector matrix, then directional division is performed for the matrix, and connected domains are searched finally, so as to find a foreground object of which motion direction or speed is different from the motion direction or speed of the background, thereby completing a search process for the foreground object. A continuous vector quantification method and a division method in the present invention can well perform analysis processing for an optical flow vector field. The foreground detection method of the present invention which obtains the foreground object through comparison of the areas of the connected domains is a method for quickly capturing the position of the foreground in the case of uncertain foreground object.

Description

technical field [0001] The invention relates to a foreground detection method, in particular to an image content retrieval method based on dense optical flow and direction division. Background technique [0002] With the coverage of video surveillance systems and the popularity of handheld mobile camera equipment such as mobile phones, video data is growing at an alarming rate, and how to extract valuable information from a large number of video files has become an urgent problem to be solved. [0003] Background modeling and object tracking are the foundation of video analysis. Background modeling distinguishes and recognizes the foreground and the background based on whether the background and the foreground are different in motion, motion direction, and color, and the target tracking realizes the real-time tracking of the target based on the characteristics of the target and the difference between the front and rear frames of the video generated by its motion. track. ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/20
CPCG06T2207/10016
Inventor 蒋兴浩孙锬锋林佳晨欧昕钺
Owner SHANGHAI JIAO TONG UNIV
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