Human motion recognition method based on plum group characteristics and a convolutional neural network

Abstract

The invention relates to a human motion recognition method based on plum group characteristics and a convolutional neural network, and belongs to the field of computer mode recognition. The method comprises the following steps: S1, data acquisition: extracting human skeleton information by utilizing micro soft body sensing equipment Kinect, and acquiring motion information of an experimenter; s2,extracting plum group characteristics, A plum group skeleton representation method for simulating a relative three-dimensional geometrical relationship between limbs of a human body by utilizing rigidlimb transformation is adopted. human body actions are modeled into a series of curves on the plum group, and then the curve based on the plum group space is mapped into a curve based on the plum algebra space through logarithm mapping in combination with the corresponding relation between the plum group and the plum algebra; and S3, feature classification: fusing the plum group features and theconvolutional neural network, training the convolutional neural network by using the plum group features, and enabling the convolutional neural network to learn and classify the plum group features, thereby realizing human body action recognition. According to the invention, a good identification effect can be obtained.

Description

technical field [0001] The invention belongs to the field of computer pattern recognition, and relates to a human body action recognition method based on Lie group features and a convolutional neural network. Background technique [0002] With the rapid development of science and technology, more natural human-computer interaction has become an increasingly urgent need for people. People are more eager for computers to think and understand the signals input from the outside world like the human brain, and understand human daily behaviors, so as to facilitate more Communicate with computers easily and naturally. [0003] Human action recognition refers to a practical technology that uses digital images or video signal streams as objects to obtain human action information through image processing and automatic recognition. Due to the variability of human body movements, camera movement, light intensity changes, differences in different human body types, and differences in hum...

AI Technical Summary

Problems solved by technology

[0008] In view of this, the object of the present invention is to provide a human body action recognition method based on Lie group features and convolutional neural network, which greatly overcomes the interference of traditional technologies on external environment changes and human body shape changes, etc., and can be compared It overcomes the defects that some action recognition methods based on traditional Euclidean space cannot simulate and express the spatial complexity and geometric relationship of human actions; at the same time, this method can better deal with the similarity between actions and the high variability between classes; In terms of computing cost and recognition effect, using convolutional neural network to process features can not only learn and classify features well, but also reduce computing cost to a large extent; the recognition accuracy is high

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