Machine learning security monitoring video occlusion intelligent filling method and system

Abstract

The invention provides a machine learning security and protection monitoring video occlusion intelligent filling method and system, and the method comprises the steps: defining an N * M grid matrix template, and putting the grid matrix template into each frame of video image, which has occlusion for a specific target, in a security and protection monitoring video; calculating the characteristic quantity of an image area where each grid in the grid matrix template is located, and combining the characteristic quantities of all grids in the grid matrix template to obtain an N * M grid matrix vector of the grid matrix template; performing clustering calculation on all the grid matrix vectors of all the video frames, and performing class cluster division; and determining a class cluster where the specific target is located, and filling the characteristic quantity of the shielded part of the specific target in each frame of video picture according to the characteristic quantity extracted from the unshielded part of the specific target in the class cluster. According to the method, the specific target is filled through the non-shielding part of the specific target in each video frame, sothat the problem of identification failure when the specific target is continuously shielded is solved.

Description

technical field [0001] The invention belongs to the technical field of video monitoring, and in particular relates to a machine-learning method and system for intelligent filling of security monitoring video occlusion. Background technique [0002] For security monitoring application scenarios, the recognition, extraction, and tracking of specific targets (such as specific people, specific vehicles) from video frames are a basic function. In the above recognition, extraction, and tracking process, first set a picture frame of an appropriate size, then intercept a part of the picture area with the picture frame from each frame of video frame, and extract feature quantities (such as contour features, color, etc.) from the picture area. feature, texture feature, etc.), and compare it with the feature threshold corresponding to the specific target. If the feature value is greater than the threshold, it indicates that the picture area where the frame is located is the position of...

AI Technical Summary

Problems solved by technology

[0004] In view of this, the present invention provides a machine learning method and system for intelligent filling of security monitoring video occlusion. For a security monitoring video, when a specific target is continuously blocked by an occluder, the specific target in each video frame Non-occluded parts, fill in the specific target, and solve the problem of recognition failure when the specific target is continuously occluded

Images