Characteristic Analysis Technology of Moving People Based on Image Recognition

Abstract

In recent years, the visual analysis of human motion has become a frontier direction in the field of computer vision. It recognizes, identifies, and tracks people in image sequences, as well as understands and describes their actions. Using computer vision technology to study the field of image processing and pattern recognition, as well as extracting and effectively identifying human motion features from video images, has become a hot topic of concern with the rapid development and popularization of information technology. This study presents a method for analyzing the characteristics of moving human bodies based on image recognition, introduces the extraction function method, and analyzes the characteristics of the extraction function to improve the ability to analyze the characteristics of moving human bodies. To achieve fine segmentation, the hierarchical clustering algorithm is used to segment the periodic motion in each motion. Different benchmark databases and self-built data were used in the experiments. Experiments show that the algorithm can achieve good classification and recognition results while maintaining low computational complexity and extracting less feature data. It can also organically integrate the static and dynamic features of human walking.