Moving object behavior tracking method, device, apparatus, and readable storage medium

Abstract

The embodiment of the invention discloses a moving target behavior tracking method, a device, a device and a computer-readable storage medium. The method includes invoking the pre-constructed object detection model to detect the object in the moving object image so as to locate the position of the moving object in the moving object image. The target detection model is based on YOLOv3 algorithm andtrained with regularization and binary cross entropy as loss function. The target detection model selects the target boundary box satisfying the preset conditions according to the intersection ratioand non-maximum suppression algorithm, and determines the center coordinate of the target boundary box to locate the position of the moving target. The present application utilizes an object detectionimage model to locate a moving object in a captured moving object image, and for a plurality of successive frames of successive images, by locating a moving object in each frame of the images, tracking detection of a moving object behavior in a video is realized. The present application improves the detection speed and positioning accuracy of a moving object.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of image processing, and in particular, relate to a method, device, equipment, and computer-readable storage medium for tracking a moving target behavior. Background technique [0002] With the continuous development of information technology, online courses are also popularized, and the research on teaching quality is more convenient. In order to better study the effect of teaching, it is particularly important to track the behavior of students and teachers. The tracking effect can be used for teaching improvement and real-time recording and broadcasting control. As a result, many manufacturers and research institutions saw the huge business opportunities contained in it, and thus began the development of intelligent classroom video recording and broadcasting systems, and many colleges and universities across the country began to establish their own laboratories. After more than ten y...

AI Technical Summary

Problems solved by technology

[0004] Although the Faster-RCNN algorithm can realize the behavior tracking and detection of moving objects, the architecture of the algorithm is relatively complex and has high requirements on the terminal, so it is difficult to implement in video or application scenarios that require faster recognition of objects

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