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Video image foreground detection method for traffic intersection scene and based on network physical system

A technology for physical systems and traffic intersections, applied in traffic flow detection, instruments, character and pattern recognition, etc., can solve problems such as inability to correctly guide the background learning process, and achieve the effect of avoiding image processing steps

Inactive Publication Date: 2013-02-13
BEIHANG UNIV
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Problems solved by technology

Even if the improved algorithm mentioned above has the ability to adjust the learning rate online, if only the brightness information of the image is used, it will not be able to correctly guide the background learning process in this scene.

Method used

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  • Video image foreground detection method for traffic intersection scene and based on network physical system
  • Video image foreground detection method for traffic intersection scene and based on network physical system
  • Video image foreground detection method for traffic intersection scene and based on network physical system

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Embodiment Construction

[0031] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0032] Such as figure 1 Shown, the specific operation process of the present invention is as follows:

[0033] (1) The calculation unit acquires the video sequence from the still camera, initializes the parameters of the background model, including the parameters of the mixed Gaussian background model: the number of Gaussian models K=5, the learning rate α=0.005, the standard deviation σ=30, and the mean value μ is passed through the average frame method to get.

[0034] (2) Lane line detection, because traffic light signals will have different effects on different lanes, so the calculation unit divides the video image area through the lane line detection algorithm, and obtains the area set φ={γ 1 , gamma 2 ,…, γ M}( i Indicates the i-th region of interest, M is the total number of obtained regions of interest, 1≤i≤M), as the basis for subsequent adjustment of t...

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Abstract

The invention discloses a video image foreground detection method for a traffic intersection scene and based on a network physical system, wherein the main application scene is an intersection in the urban traffic. The method mainly comprises the following steps of: performing lane line detection in the extracted background frame and dividing an area of interest according to a video image obtained by a static video camera in the system; adjusting the background learning process and the learning rate of the pixel points of different image areas by use of the external information sensed by the system; and adaptively adjusting the parameters in the algorithm in real time to finally obtain a more accurate foreground point detection result. The method disclosed by the invention realizes adaptive adjustment of the background learning rate according to the physical environment under the condition of complicated varying foreground speed in the scene of the urban traffic intersection.

Description

technical field [0001] The invention relates to the fields of intelligent transportation, video image processing and machine vision, in particular to a video image foreground detection method for traffic intersection scenes and based on a network physical system. Background technique [0002] The foreground detection method has always been an important research content in the field of video surveillance and image processing. It is the basis of subsequent processing and directly affects higher-level applications, such as interest target tracking, behavior analysis, anomaly detection, etc. There are two types of foreground detection algorithms: frame difference method and background difference method. The frame difference method is fast and can accurately obtain the edges of moving objects, but there are many holes in the foreground objects obtained. For fast-moving objects, smearing will occur during detection, and static objects cannot be detected. [0003] Background Subtr...

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Application Information

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IPC IPC(8): G08G1/01G06K9/66
Inventor 丁嵘刘旭崔伟龙贺百灵
Owner BEIHANG UNIV
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