基于近似字符串匹配的姿势识别算法  

Posture Recognition Algorithm Based on Approximate String Matching

作　　者：王绍雷 杨鹤标[1] WANG Shao-Lei;YANG He-Biao(School of Computer Science and Communication Engineering,Jiangsu University,Zhenjiang 212013,China)

机构地区：[1]江苏大学计算机科学与通信工程学院,江苏镇江212013

出　　处：《软件导刊》2018年第9期101-105,109,共6页Software Guide

基　　金：江苏省社会发展项目(BE2017700)

摘　　要：近似字符串匹配算法string-k是一种高效的基于模板类的人体姿势识别算法,其实时性能能保障在低端设备(如智能手机、平板等)上完美运行。由于该算法的识别率偏低,难以满足用户体验。为此,提出一种优化的姿势识别算法。算法基本思想是:剔除与姿势相关度低的骨骼节点,依据骨骼节点对识别姿势贡献度的大小分配相应权值,采用改进的Levenshtein距离计算姿势序列降低识别过程的计算量。实验结果表明,在保证实时性条件下,提高了多数姿势的识别率。Approximate string matching algorithm string-k is an efficient template-based human pose recognition algorithm.It can smoothly run in low computing capability devices （smartphone,tablets etc.） with real-time performance.But it can not meet users＇ requirements because of its low recognition rate.Therefore,an optimized human post recognition algorithm is proposed.The basic idea of this algorithm is to remove the skeleton nodes with low relevancy to the pose,and adopt the improved Levenshtein distance calculation Posture sequence to reduce the computational complexity of the recognition process.Experimental results show thatthe algorithm can improve the recognition rate of most posts by ensuring the real-time performance.

关 键 词：姿势识别 骨骼节点 string-k MSRC-12 Levenshtein距离 

分 类 号：TP312[自动化与计算机技术—计算机软件与理论]