徐州工程学院学报（自然科学版）2025，Vol.40Issue(4)：50-56,7.
基于优化HMM的人体运动姿态识别研究
Human Motion Posture Recognition Based on Optimized Hidden Markov Model
摘要
Abstract
To improve the accuracy with which human motion postures are recognized,this paper proposes a method based on an optimized Hidden Markov Model(HMM).Standards for recognizing these postures are set based on the positional relationship between joints and bones in different postures.Optical imaging is used to capture human motion.The initial images are pre-processed using steps such as grayscale conversion and noise reduction.Motion targets are then detected and tracked,and posture features are extracted using the optimized HMM.Human motion posture recognition is then achieved based on state probability and feature matching results.Performance tests conclude that the optimized design method achieves an average recognition error rate of 0.13％.making it superior to traditional methods.关键词
优化HMM/人体运动/运动姿态/姿态识别方法Key words
optimized HMM/human motion/motion posture/posture recognition method分类
信息技术与安全科学引用本文复制引用
REN Yuanbo,CAO Yao,SUN Anping..基于优化HMM的人体运动姿态识别研究[J].徐州工程学院学报（自然科学版）,2025,40(4):50-56,7.基金项目
安徽省质量工程项目(2021jyxm1229) （2021jyxm1229）
安徽省高校哲学社会科学研究项目(2022AH052114) （2022AH052114）
合肥师范学院质量工程项目(2021szjy12) （2021szjy12）
合肥师范学院科研项目(2021SKQN10) （2021SKQN10）
合肥市企业委托项目(HXXM2022078) （HXXM2022078）
