Video behavior recognition method based on weighted fusion of multiple image tasks

Abstract

The invention relates to a video behavior recognition method based on weighted fusion of multiple image tasks. The video behavior recognition method comprises the following specific steps: 1, constructing an initialized teacher network; 2, downloading and selecting a plurality of pre-training models and parameters of a visual image task common data set in positive correlation with video behavior identification as an initialized teacher network; 3, establishing a multi-teacher video behavior recognition knowledge base; 4, under the guidance of the multi-teacher network with the weight distributed again, carrying out self-supervised training based on comparative learning on the student network; 5, carrying out performance test on the model video behavior identification on the test data set. The method has the advantages that the image task in positive correlation with the video behavior recognition task serving as the target task is used as the teacher task, the training mode of comparison self-supervised learning is adopted, and the video behavior recognition problem under the condition that high-quality video marking samples are insufficient is solved. Therefore, the accuracy of video behavior identification is effectively improved.

Description

technical field [0001] The invention relates to the technical field of video behavior analysis, in particular to the design of a video behavior recognition method for weighted fusion of multiple image tasks. Background technique [0002] Behavior recognition is an attractive and challenging research direction in recent years, that is, given a cropped video, judge the human behavior category in this video through computer vision technology. The development of deep convolutional neural networks and the emergence of large-scale labeled datasets in recent years have significantly improved the accuracy of action recognition. Behavior recognition technology is playing an increasingly important role in many fields such as intelligent security, human-computer interaction, video understanding, and medical health. [0003] The existing supervised learning-based Deep Convolutional Neural Network (Deep CNN) model algorithm has achieved relatively ideal results. However, in order to ob...

AI Technical Summary

Problems solved by technology

[0010] The present invention fully considers the correlation between different visual tasks in the field of computer vision, and the characteristics that the prior knowledge of related tasks can be transferred and utilized, and proposes a video behavior recognition method for weighted fusion of multiple image tasks. The video behavior The recognition method solves the time-consuming and laborious problem of marking large-scale high-quality video training samples in the existing video behavior recognition task

Images