基于骨架运算的动态手势定位及识别算法

摘要/Abstract

摘要：

为满足在不同背景条件下用户的手势识别需求,提出了一种对于动态手势定位及识别的算法。在摄像头固定、目标移动的前提下,采用ViBe算法对背景建模后结合肤色检测,对手势目标区域进行检测。文中提出了掌心的定位方法,算法利用形态学骨架运算提取图像特征,为解决用户不同衣着和动作造成判断区域的多样性和不确定性,进行有效区域选取后定位掌心坐标,根据掌心坐标通过似圆度和掌心极坐标进行手势定位和识别。实验结果证明,所提算法能够在复杂背景下准确地对手掌高于手肘的手势判断出掌心点,分割出手掌并进行手势识别,该算法同时拥有较好的鲁棒性和实时性。

关键词: 手势识别, 手势分割, 特征提取, 抽骨架运算, 形态学运算, 掌心定位

Abstract:

A novel algorithm for dynamic hand gesture localization and recognition based on skeletonization is proposed,which satisfies the requirements of the user under different background conditions.With the presumption that pictures of the moving objects are taken by fixed camera,the ViBe algorithm combined with skin-color detection is used for detecting the hand area.In order to eliminate the variety and uncertainty caused by user's various dresses and motions,an innovation in this article is stated in the method of palm center extraction,which is skeletonizing the hand area,finding out the effective area and then the coordinate of palm center,and positioning and recognizing the hand gesture referring to the roundness and palm center polar coordinates.Experimental results demonstrate that,in the situation which the position of hand is higher than that of elbow,the algorithm works precisely under the complex background with good robustness and real-time performance.

Key words: hand gesture recognition;hand gesture segmentation;feature extraction;skeletonization;morphology;palm center localization

中图分类号:

TP391.41

刘耀杰,舒畅,傅志中. 基于骨架运算的动态手势定位及识别算法[J]. , 2014, 27(3): 7-.

LIU Yaojie,SHU Chang,FU Zhizhong. Dynamic Gesture Localization and Recognition Algorithm Based on Skeletonization[J]. , 2014, 27(3): 7-.

参考文献

［1］李文生.解梅.邓春健.基于机器视觉的动态多点手势识别方法［J］.计算机工程与设计,2012,33(5):1988-1992.

［2］曹雏清,李瑞峰,赵立军.基于深度图像的手势识别方法［J］.计算机工程,2012,38(8):16-21.

［3］翁汉良,战荫伟.基于视觉的多特征手势识别［J］.计算机工程与工程,2012,34(2):123-127.

［4］杨扬,程楠楠,张萌萌.基于平均领域最大化的手势识别方法研究［J］.计算机工程,2012,38(9):19-35.

［5］安涛.彭进业.吴静.基于Haar小波分解的实时手势识别［J］.计算机工程,2011,37(24):138-140.

［6］BARRON J,FLEET D,BEACHEMIN S.Performance of optical flow techniques［J］.International Journal of Computer Vision,1994,12(1):42-47.

［7］MEIER T.NGAN K N.Automatic segmentation of moving object plane generation［J］.IEEE Tansaction on Circuit and Systems for Video Technology,1998,8(5):525-538.

［8］刘露平.基于视频序列动目标检测的远程视频监控系统的实现［D］.成都:电子科技大学,2013.

［9］蒋建国,王涛,齐美彬,等.基于ViBe的车流量算法［J］.电子测量与仪器学报,2012,26(6):558-563.

［10］BARNICH O V,DROOGENBROECK M.ViBe:a powerful random technique to estimate the background in video sequences［C］.Int.Conf.on Acoustics Speech and Signal Processing(ICASSP),2009,4:945-948.

［11］BARNICH O V,DROOGENBROECK M,EVS B E,et al.ViBe:a universal background subtraction algorithm for video sequences［J］.IEEE Transactions on Image Processing,2011,20(6):1709-1724.

［12］KEGL B,KRZYZAK A.Piecewise linear skeletonization using principal curves［J］.IEEE Transaction on Pattern Analysis and Machine Intelligence,2002,24(1):59-74.

［13］崔屹.图像处理和分析——数学形态学方法及应用［M］.北京:科学出版社,2000.

［14］SBASTIEN M,OLIVIER B,JEAN-EMMANUEL V,et et.Daniel collobert hand gesture recognition using input/ouput hidden markov models［C］.Grenoble:FG′2000 Conference on Automatic Face and Gesture Recognition,2000.

[1]	伍伟嘉,杨俭,袁天辰,邵志慧. 基于支持向量机的轨道结构病害识别研究[J]. 电子科技, 2022, 35(2): 27-33.
[2]	李辉,王一丞. 基于CNNCIFG-Attention模型的文本情感分类[J]. 电子科技, 2022, 35(2): 46-51.
[3]	邵志慧,杨俭,袁天辰,伍伟嘉. 基于排列熵和支持向量机的轨枕病害诊断[J]. 电子科技, 2022, 35(2): 52-58.
[4]	司明明,陈玮,胡春燕,尹钟. 融合Resnet50和U-Net的眼底彩色血管图像分割[J]. 电子科技, 2021, 34(8): 19-24.
[5]	马立新,豆晨飞,宋晨灿,杨天笑. 基于特征融合卷积神经网络的绝缘子无损检测[J]. 电子科技, 2021, 34(7): 26-30.
[6]	刘姝,邵杰,张颐婷,张善章. 基于双谱和谱特征的心电信号分类方法[J]. 电子科技, 2021, 34(5): 42-46.
[7]	宋章明,贺慧勇,黄跃俊. 扁平漆包线表面缺陷在线检测研究[J]. 电子科技, 2021, 34(5): 72-78.
[8]	李兆基,王海鹏,阮伟华,黄书豪. 辅助虚拟现实数据手套及电刺激力触觉增强反馈电路系统设计[J]. 电子科技, 2021, 34(3): 28-36.
[9]	葛靖,刘子龙. 基于CNN和LSTM的睡眠呼吸暂停检测算法[J]. 电子科技, 2021, 34(2): 21-26.
[10]	巨志勇,翟春宇,张文馨. 基于SVM与区域生长的彩色商品标签图像分割方法[J]. 电子科技, 2021, 34(10): 69-74.
[11]	刘义民,刘韬,陈庆. CHMM和AR模型在轴承性能退化评估与预测中的应用[J]. 电子科技, 2020, 33(5): 58-65.
[12]	司琴,李菲菲,陈虬. 基于深度学习与特征融合的人脸识别算法[J]. 电子科技, 2020, 33(4): 18-22.
[13]	王正军,姚一鸣,陈龙. 基于卷积神经网络的PCB板通用分拣算法[J]. 电子科技, 2020, 33(2): 60-65.
[14]	王贺贺,李菲菲,陈虬. 基于稠密轨迹特征的动态手势识别研究[J]. 电子科技, 2020, 33(12): 17-21.
[15]	邵玉娥,王暕来,周生华,刘宏伟,张月红. 基于LASSO的雷达脉压压缩方法[J]. 电子科技, 2020, 33(11): 7-10.