计算机应用与软件2013，Vol.30Issue(3)：244-246,254,4.DOI:10.3969/j.issn.1000-386x.2013.03.064
基于Haar小波和融合HMM的步态识别方法
GAIT RECOGNITION METHOD BASED ON HAAR WAVELET AND FUSED HMMS
李萍1
作者信息
- 1. 陕西学前师范学院计算机科学与技术系 陕西西安710000
- 折叠
摘要
Abstract
This paper presents a novel gait recognition approach based on Haar wavelet and fused hidden Markov model. It solves the problem that in gait recognition there are insufficient key points of the gait feature in each region. First, the approach converts images from video sequences to binary contour, and uses Haar wavelet transform to obtain the distinct key points of gait features. Then two sub-images are utilised to represent the gait feature of each contour, and the principal component analysis is employed to reduce the number of dimensions. Finally, fused hidden Markov model is used for training and testing. Simulation result indicates that the approach can simplify the process of gait identification, and can also improve the recognition accuracy.关键词
特征提取/步态识别/Haar小波域/隐融合马尔可夫模型Key words
Feature extraction/ Gait recognition / Haar wavelet/ Fused hidden Markov models (FHMM)分类
信息技术与安全科学引用本文复制引用
李萍..基于Haar小波和融合HMM的步态识别方法[J].计算机应用与软件,2013,30(3):244-246,254,4.
