Hybrid neural network-based gesture recognition method

Abstract

The invention discloses a hybrid neural network-based gesture recognition method. For a gesture image to be recognized and a gesture image training sample, first a pulse coupling neural network is used to detect to obtain noise points, then a composite denoising algorithm is used to process the noise points, then a cell neural network is used to extract edge points in the gesture image, connected regions are obtained according to the extracted edge points, curvature is used to perform fingertip detection on each connected region to obtain undetermined fingertip points, interference of a face part is eliminated to obtain a gesture region, then the gesture region is partitioned according to gesture shape features, Fourier descriptors which keep phase information are obtained according to contour points of the partitioned gesture region, and first multiple Fourier descriptors are selected as gesture features; and a BP neural network is trained according to gesture features of the gesture image training sample, and the gesture features of the gesture image to be recognized are input to the BP neural network for recognition. The hybrid neural network-based gesture recognition method provided by the invention improves the accuracy rate of gesture recognition through utilization of various neural networks.

Description

technical field [0001] The invention belongs to the technical field of gesture recognition, and more specifically relates to a gesture recognition method based on a hybrid neural network. Background technique [0002] With the rapid development of computer technology, human-computer interaction technology is becoming more and more popular in people's life. Human-computer interaction (Human-Computer Interaction, HCI) technology refers to an interactive process between a human and a computer that is performed by using a certain operation mode between the user and the computer. Its development has roughly gone through the pure manual operation stage, the language command control stage, the user interface stage, etc. However, with the continuous development of artificial intelligence and other technologies in recent years, it has gradually attracted attention to the development of human-computer interaction technology. [0003] Now with the continuous expansion of computer appl...

AI Technical Summary

Problems solved by technology

However, the application of neural network methods in the field of gesture behavior recognition is limited to the stage of gesture recognition, and there are few applications in other stages of gesture behavior recognition.

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