|本期目录/Table of Contents|

[1]田秋红,杨慧敏,梁庆龙,等.视觉动态手势识别综述[J].浙江理工大学学报,2020,43-44(自科四):557-569.
 TIAN Qiuhong,YANG Huimin,LIANG Qinglong,et al.Overview on visionbased dynamic gesture recognition[J].Journal of Zhejiang Sci-Tech University,2020,43-44(自科四):557-569.
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视觉动态手势识别综述()
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浙江理工大学学报[ISSN:1673-3851/CN:33-1338/TS]

卷:
第43-44卷
期数:
2020年自科四期
页码:
557-569
栏目:
出版日期:
2020-07-10

文章信息/Info

Title:
Overview on visionbased dynamic gesture recognition
文章编号:
1673-3851 (2020)07-0557-13
作者:
田秋红杨慧敏梁庆龙包嘉欣
浙江理工大学信息学院,杭州 310018
Author(s):
TIAN QiuhongYANG HuiminLIANG Qinglong BAO Jiaxin
School of Informatics Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018,China
关键词:
视觉动态手势识别综述手势分割手势追踪特征提取手势分类
分类号:
TS195-644
文献标志码:
A
摘要:
基于视觉的动态手势识别是人机交互领域应用较为广泛的技术,其发展对于实现人机自然交互有着重要研究意义。文章介绍并分析了目前常用的手势交互系统。通过对近年来国内外相关文献的领域研究进行梳理,概述了视觉动态手势识别的一般流程,其流程包括检测与分割、追踪、特征提取、分类,并对各流程所涉及的方法及优缺点进行了对比分析;探讨了视觉动态手势识别研究所面临的挑战性问题和未来可能的研究方向,为推动该领域的进一步研究提供参考。

参考文献/References:

[1] 武霞, 张崎, 许艳旭. 手势识别研究发展现状综述[J]. 电子科技, 2013, 26(6): 171-174.
[2] Hassan M, Assaleh K, Shanableh T. Userdependent sign language recognition using motion detection[C]//2016 International Conference on Computational Science and Computational Intelligence (CSCI). Las Vegas: IEEE, 2016: 852-856.
[3] Hyun D, Jegal M, Yang H S. Compact selfcontained navigation system with MEMS inertial sensor and optical navigation sensor for 3D pipeline mapping[C]//2010 IEEE/RSJ International Conference on Intelligent Robots and Systems. Taipei: IEEE, 2010: 1488-1493.
[4] Cao Y, Xi Z W. A review of MEMS inertial switches[J]. Microsystem Technologies, 2019, 25(12): 4405-4425.
[5] Ciuti G, Ricotti L, Menciassi A, et al. MEMS sensor technologies for human centred applications in healthcare, physical activities, safety and environmental sensing: a review on research activities in Italy[J]. Sensors, 2015, 15(3): 6441-6468.
[6] Zhang X, Chen X, Li Y, et al. A framework for hand gesture recognition based on accelerometer and EMG sensors[J]. IEEE Transactions on Systems, Man, and CyberneticsPart A: Systems and Humans, 2011, 41(6): 1064-1076.
[7] Moin A, Zhou A, Benatti S, et al. Adaptive EMGbased hand gesture recognition using hyperdimensional computing. (2019-08-30)[2019-12-28]. https://arxiv.org/abs/1901-00234.
[8] Li H, Yang W, Wang J, et al. WiFinger: talk to your smart devices with fingergrained gesture[C]//Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. Heidelberg: 2016: 250-261.
[9] Wang F X, Gong W, Liu J C, et al. Channel selective activity recognition with WiFi: A deep learning approach exploring wideband information[J]. IEEE Transactions on Network Science and Engineering, 2020, 7(1): 181-192.
[10] Ji Y, Kim S,Lee K B. Sign language learning system with image sampling and convolutional neural network[C]//2017 First IEEE International Conference on Robotic Computing (IRC), Taiwan: IEEE, 2017: 371-375.

备注/Memo

备注/Memo:
收稿日期:2019-12-28
网络出版日期:2020-04-02
基金项目:国家自然科学基金项目(51405448);浙江理工大学博士科研启动项目(11122932611817);浙江省大学生科技成果推广项目(14530031661961);浙江理工大学国家级大学生创新创业训练计划项目(201910338012)
作者简介:田秋红(1976-),女,辽宁兴城人,博士,主要从事图像处理和模式识别方面的研究
更新日期/Last Update: 2020-07-06