Improved visual background extraction method based on blind updating strategy and foreground model

A technology of visual background extraction and foreground model, which is applied in the field of improved visual background extraction based on blind update strategy and foreground model, can solve the problems of time-consuming, undetectable, ghosting, etc., and achieve the effect of improving the accuracy rate

Active Publication Date: 2016-07-06
ZHEJIANG UNIV OF TECH
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AI Technical Summary

Problems solved by technology

However, if there is a moving object in the first frame of video, the initialization of the moving area will use the pixel set of the moving object to model, causing deadlock and ghosting
Another blind update mechanism uses foreground points and background points to update the background model, which is not sensitive to deadlock, but the disadvantage is that slow moving objects in the video scene will be integrated into the background model and cannot be detected
Although the ViBe method adopts the strategy of updating the neighborhood background model in a diffuse manner and counting the foreground to eliminate the ghosting phenomenon, it still takes a certain amount of time and affects the accuracy of the foreground detection.

Method used

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  • Improved visual background extraction method based on blind updating strategy and foreground model
  • Improved visual background extraction method based on blind updating strategy and foreground model
  • Improved visual background extraction method based on blind updating strategy and foreground model

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Embodiment Construction

[0021] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0022] The invention is an improved foreground detection method based on the ViBe method. By adopting a blind update strategy and establishing a foreground model, the problem that slow moving objects are difficult to detect is solved, and the correct detection rate of foreground points is effectively improved while ensuring the real-time performance of the method. The flow chart of the method is as figure 1 As shown, its specific implementation is as follows:

[0023] Step 1: Input the video sequence and read the first frame; use a single frame image to initialize the background model, and use the temporal and spatial similarity characteristics of neighboring pixels to randomly select N b (experimental data N b =20) pixels as the sample points of its model.

[0024] Step 2: Establishment of the foreground model. To be precise, the foreground model sh...

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Abstract

An improved visual background extraction method based on a blind updating strategy and a foreground model comprises the following steps: S1, reading the first frame of a video, and initializing and building a background model; S2, initializing and building a foreground model; S3, reading a new video frame, judging whether a point is classified as a background point according to the background model, and making classification judgment on the point based on the foreground model if the point is classified as a background point; S4, processing a binary foreground image through morphological filtering; S5, updating the foreground model and the background model; and S6, reading a new video frame, repeating S3 to S5, and detecting a moving foreground area in a video sequence in real time.

Description

technical field [0001] The invention relates to a foreground detection method for moving objects in video. Background technique [0002] With the development of modern security monitoring systems, more and more video monitoring technologies have been widely used in commercial places, tourist attractions and traffic monitoring and other fields. The main technologies include moving target detection, moving object recognition, target tracking, behavior analysis and pedestrian monitoring. counting etc. Among them, moving target detection is the basis of follow-up research, which directly affects the quality of follow-up research results. At present, due to the needs of the development of monitoring technology, many foreground detection methods have been developed, such as: frame difference method, background subtraction method (GMM, CodeBook, SOBS, ViBe), optical flow method (sparse optical flow, dense optical flow), time entropy etc. These methods have their respective adapt...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/20
Inventor 王海霞石丽梁荣华毛帅龙
Owner ZHEJIANG UNIV OF TECH
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