Video based motion pattern detection method and device

Abstract

The invention belongs to the video monitoring field and provides a video based motion pattern detection method and device. The video based motion pattern detection method comprises obtaining a video image; estimating a motion foreground image, wherein the estimation of the motion foreground image specifically comprises establishing a preliminary motion foreground image, extracting a contour image of the motion foreground image and establishing a motion history image for the contour image; detecting a moving target of the motion foreground image; updating the state of the moving target. The video based motion pattern detection device comprises an image acquisition module, a motion foreground estimation module connected with the image acquisition module, a moving target detection module connected with the motion foreground estimation module and a target state update module connected with the moving target detection module. According to the video based motion pattern detection method and device, the problems of the slow background update caused by background modeling and the serious prospect cavity are solved, the accurate and stable continuous counting on the movement displacement and movement direction can be achieved, and the effective accurate information can be provided for application development.

Description

technical field [0001] The invention relates to the field of video monitoring, in particular to a video-based motion pattern detection method and device. Background technique [0002] Accurate estimation of target motion information based on video has a wide range of applications in the field of actual video analysis, especially in teaching monitoring. It is very meaningful to accurately estimate the motion information of the target in a specific direction. prerequisite for accurate positioning. At present, the mainstream methods for estimating the amount of motion in a specific direction of the target are mainly based on methods such as optical flow and background modeling. Usually, the dense optical flow field of the whole image is calculated, and then the dense optical flow field is divided to extract the motion block, and the motion displacement and direction of the target are calculated. The disadvantage of this method is that it has a large amount of calculation, and...

AI Technical Summary

Problems solved by technology

However, this method mainly has the following shortcomings. First, the background modeling for the complex environment of the classroom often leads to poor background effects, and it is easy to produce empty moving objects, and the background update is extremely slow; second, this method is simple. The accuracy of the statistical target displacement is not high, and other information, such as the direction of target movement, is not extracted, which cannot provide effective and accurate information for subsequent application development

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