Neural network-based movement recognition method

Abstract

The invention discloses a neural network-based human body movement recognition method. The method includes the following steps of based on a video database, training N mutually independent 3D convolutional neural networks as a video feature extractor; according to the video feature extractor, training a multi-instance learning classifier; inputting a to-be-recognized video, extracting video features through the well trained network, and classifying movements by the classifier. According to the technical scheme of the invention, the influence of a large amount of noise features on a classification result is avoided. Meanwhile, the negative effect of a fixed sample length on a movement recognition result is also avoided.

Description

technical field

[0001] The invention relates to the field of human action recognition, in particular to an action recognition method based on a neural network. Background technique

[0002] With the development of the mobile Internet, the carrier of information has gradually expanded from text to audio, image, video and other forms. In recent years, the amount of video data has grown explosively, and the application fields have become more diverse, involving various fields such as security, surveillance, and entertainment. [1] . Faced with such a massive amount of data, traditional manual processing can no longer meet people's needs. Therefore, using the computer's powerful storage and computing capabilities to realize the recognition and understanding of video information has important academic value and broad application prospects.

[0003] In fact, in the field of computer vision, research on video has been carried out for decades, and research topics include action re...

Images