A method, system and device for dynamic background differential detection based on spatiotemporal classification

Abstract

The invention discloses a space-time classification-based dynamic background differential detection method, a system and a device. The method comprises the steps of establishing a background model corresponding to each pixel in an image through packet sampling in a time sequence, classifying pixels in the background model according to to-be-detected pixels and obtaining a rough foreground mask image; with a foreground pixel point in the rough foreground mask image as a center, classifying pixel points in a preset neighboring domain range of the central pixel point, and correcting the central pixel point to be a background pixel point or still maintaining the central pixel point as a foreground pixel point according to the number of pixel points the same type with the central pixel point within the preset neighboring domain range of the central pixel point and belonging to background pixel points. According to the invention, the packet sampling method is adopted, so that the ability ofthe dynamic background description is enhanced. Only pixel points the same type of the central pixel point are adopted to judge whether a foreground pixel point is a real foreground pixel point or not. Therefore, the accuracy of detection is improved. The method can be widely applied to the field of moving target detection.

Description

technical field [0001] The invention relates to the field of moving target detection, in particular to a dynamic background difference detection method, system and device based on spatiotemporal classification. Background technique [0002] Moving target detection is the basis of target recognition, tracking and subsequent understanding of object behavior, and is a research hotspot in the field of computer vision. The background subtraction method (also known as the background subtraction method) is the most commonly used method in moving object detection. The basic principle is to realize the moving object detection by making a difference between the current frame image and the background image. The background difference method is fast, accurate and easy to implement when detecting moving targets. The key is the acquisition of the background image. In practical applications, affected by factors such as sudden changes in illumination, fluctuations of some objects in the act...

AI Technical Summary

Problems solved by technology

Methods based on local texture features segment the foreground object and background according to the texture smoothness of different components in the video scene. The limitation of this type of method is that it needs to manually design features with good discrimination

Therefore, the background difference method combined with spatial neighborhood information (ie, the second type of method) is useful for dynamic backgrounds with frequent movements because of the use of pixel neighborhood spatial information (ie, regional features) when detecting dynamic background and foreground objects. Good robustness, but it also uses all the neighboring pixels of the pixel to describe the background pixels. If some of the neighboring pixels of the pixel are foreground pixels, it will affect the detection effect and reduce the detection accuracy

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