Behavior recognition and positioning method based on multi-task joint learning

Abstract

The invention discloses a behavior recognition and positioning method based on multi-task joint learning. A convolutional neural network in deep learning is combined with multi-task joint learning toreplace a single-task convolutional-neural-network algorithm to achieve the goal of human body behavior recognition and behavioral positioning in a video. The method improves an object detection deep-network in faster rcnn, combines a behavior recognition deep-network on the basis thereof, enables a combined network to achieve capability of multi-task joint learning, enables two tasks to promote each other, and enhances robustness and accuracy of a recognition algorithm; at the same time, the method combines a video data set and a picture data set, and enhances information diversity of a training set; and in addition, huge energy can be consumed if human body positions in the video data set are labeled, but the method can omit labeling work of the data set through self-learning of the algorithm, and can greatly reduce labeling workloads.

Description

technical field [0001] The invention belongs to the technical fields of computer vision, machine learning and deep learning, and specifically relates to the design of a behavior recognition and positioning method based on multi-task joint learning. Background technique [0002] In the field of security, there is a great demand for human behavior detection and positioning, such as the detection of violent behavior. If the violent behavior that endangers society and others can be detected in real time and measures taken, it will be of great significance to social stability. If it is possible to locate the specific thugs who committed violent acts in the video, combined with the application of face recognition, it will be of great value to quickly solve the case. However, the current video surveillance system is mainly based on manpower and supplemented by computers. It mainly identifies the content of the surveillance video manually. The workload is huge, and as the surveillan...

AI Technical Summary

Problems solved by technology

[0008] The purpose of the present invention is to solve the above-mentioned problems in the prior art, and propose a behavior recognition and positioning method based on multi-task joint learning, which uses the combination of convolutional neural network in deep learning and multi-task joint learning to replace a single task Convolutional neural network algorithm to meet the needs of human behavior recognition and behavior positioning in video clips

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