Method, apparatus, computer device and storage medium for classifying video actions

Abstract

The invention relates to a method, an apparatus, a computer device and a storage medium for classifying video actions, belonging to the technical field of machine learning models. The method comprisesthe following steps: obtaining a video to be classified and determining a plurality of video frames in the video to be classified; A plurality of video frames are inputted into an optical flow substitution module in an optimized video motion classification model after training, and optical flow characteristic information corresponding to the plurality of video frames is obtained. A plurality of video frames are input into a three-dimensional convolution neural module in the optimized video motion classification model after training, and the spatial characteristic information corresponding tothe plurality of video frames is obtained. Based on the optical flow characteristic information and the spatial characteristic information, the classification category information corresponding to thevideo to be classified is determined. By adopting the invention, a plurality of video frames of a video to be classified can be directly used as inputs of an optical flow substitution module in the model, and the optical flow substitution module can directly extract optical flow characteristic information corresponding to the plurality of video frames of the video to be classified, thereby further improving the efficiency of classification processing.

Description

technical field [0001] The present disclosure relates to the technical field of machine learning models, and in particular to a video action classification method, device, computer equipment and storage medium. Background technique [0002] With the development of society, more and more users like to use fragmented time to watch or shoot short videos. When any user uploads a short video shot to the short video platform, relevant personnel in the short video platform can view the short video and classify the actions of the objects in the short video according to subjective ideas, such as dancing, climbing trees, drinking water etc. Then, relevant personnel can add corresponding tags to the short video according to the classification results. [0003] In the process of realizing the present disclosure, the inventors found at least the following problems: [0004] Due to the huge number of short videos received by the short video platform, if the actions of objects in each s...

AI Technical Summary

Problems solved by technology

[0004] Due to the huge number of short videos received by the short video platform, if the actions of the objects in each short video are manually classified, the efficiency of the classification operation will be extremely low

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