Moving object detection method and device based on space-time background model

Abstract

The invention provides a moving object detection method based on a space-time background model. The method comprises the steps that 1, a time background model is obtained by collecting image modeling; 2, initial moving objects are obtained; 3, a background region of grown initial moving objects is obtained; 4, the space background model is obtained; 5, whether space-time model distribution is conformed or not is judged; 6, the time background model is updated. The invention further provides a moving object detection device based on the space-time background model, the moving object detection device comprises an image acquisition module, a time background modeling module, a moving object detection module, a space background modeling module, a moving object confirmation module and a background model updating module. The invention provides a space background modeling concept, it is considered that foreground objects and surrounding backgrounds have certain differences on features such as color, if the initial moving objects are in accordance with the surrounding backgrounds on the color feature, it is considered to be false detection, and the accuracy of moving object detection is improved.

Description

technical field [0001] The invention relates to the field of intelligent video monitoring, in particular to a method and device for detecting a moving object based on a spatio-temporal background model. Background technique [0002] The basic task of moving target detection is to extract the moving target from the image background from the sequence of images, so as to obtain the moving information of the target, which is of great significance to the subsequent work of image classification, target tracking, etc., and can be used to a large extent Simplify analysis work. Because in the actual monitoring scene, the background is often not completely static, but is changing all the time, such as: changes in the weather, slight and regular shaking of the background, changes in lighting, and gradually blending into the target in the background, etc., making the background construction Modeling has become an important and difficult problem in moving target detection. [0003] The...

AI Technical Summary

Problems solved by technology

These traditional background modeling methods use the statistical characteristics of pixels in time series to model, and do not make full use of spatial information. Therefore, in the process of target detection, there are often more false detections, and in the process of background update, It is easy to update the foreground into the background, and the real background does not update fast enough

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