Method for recognizing human motion

Abstract

The invention discloses a method for recognizing a human motion in the field of computer vision and pattern recognition. Firstly, a feature containing time and space information is used for expressing the motion status of a human body in a current frame, and a classifier is designed through a graph theory semi-supervised method so that the purpose of human motion recognition is achieved. In the process of extracting the human motion feature, outline and motion light stream information in the past, in the present time and in the future is simultaneously fused so that the motion posture of a human body can be more accurately described. In addition, in order to obtain a high recognition rate with a few samples, based on the graph theory semi-supervised method of the generalized Laplacian matrix, and the graph theory semi-supervised method is used for recognizing the human motion. Experiments prove that under the conditions that observation angles are different and the motion difference of different persons exists, the method can be used for obtaining the satisfactory recognition rate of common motions.

Description

technical field [0001] The invention belongs to the field of computer vision and pattern recognition, and in particular relates to a method for recognizing common human actions. Background technique [0002] In the field of computer vision, human action recognition is a newly emerging but very important branch. Its main purpose is to enable computers to automatically judge and understand the actions that the human body is currently performing. Since the computer itself does not have the high-level comprehension ability similar to human beings, computer action recognition is a very challenging task. However, the application prospect of action recognition is very broad. For example, it can play an important role in human-computer interaction, video conferencing, video retrieval, patient self-monitoring, intelligent security monitoring and other occasions. So research in this area is also very necessary. [0003] Due to various reasons, the existing action recognition effect ...

AI Technical Summary

Problems solved by technology

[0006] Because people have differences in height, body length, and behavioral posture, different people will have different ways of expressing the same action. Therefore, it is not good for an action recognition system to perform action recognition by covering all people's movement postures. practical

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