摘要
形体交流及表达等非语音类交流与语音交流有着同样的重要地位,包括人的身体姿势、头部动作、手势、注视和表情等。而计算机技术的发展使人与计算机的交流越趋频繁和复杂,以键盘和鼠标作为人机界面交流的传统方式,已无法传达出人机交流中形体所表达的细腻信息,更谈不上释放人机交流的多种潜能,于是研究符合人机交流习惯的新型交互技术也变得活跃,包括基于计算机视觉的动作识别技术。基于计算机视觉的动作识别系统,涉及到计算机科学、人工智能、神经生物物理学、认知心理学、艺术学等多门学科,本文对于新型人机交互模式的探索以及对机器人智能技术的研究势必对上述每一个学科都有不同的重要意义和影响。
首先采用归类分析法对基于计算机视觉的动作识别技术与理论进行了分析研究,这其中包括人眼的跟踪识别、人脸识别、头部动作跟踪识别、手势识别以及姿势识别等。之后比较现有动作识别方法的各种优缺点,归纳总结出目前常用人机界面在人机交流中所起的正负作用。
在上述研究基础之上,通过实验设计法,设计制作了一个基于头部动作识别的虚拟画展系统,以便深入了解基于计算机视觉的动作识别系统的每一个技术环节的基本功能和可能性,力图在实验和测试新型的人机交互模式时能够有效地分析出在新技术支持下人机交互系统的优势与不足。
最后通过总结归纳法得出了本文的最终结论,即基于计算机视觉的动作识别,能使计算机识别并理解用户的行为,在键盘鼠标等传统交流设备的基础之上,用户可以更自然地与计算机进行丰富与复杂的交流。随着技术的发展与推进,当计算机视觉具备了人眼的基本功能,计算机处理系统就可以,也能够模拟人类处理信息的方式而衍生出具有“自我进化”的能力,到那时,计算机的智能将可以达到理解人类的交流方式的地步,人与机器之间的界面也将逐渐消隐,达到“隐性人机交互”的理想状态。
Such non-verbal communication as human body communication and expression, including gazing, facial expression, head motion, gesture and posture of equal importance with the verbal communication. HM(Human Machine) Communication are getting more frequent under the development of digital technology. However, traditional keyboard-mouse interaction would not be able to explore the potential of the human body.
In the dissertation, research is done on the gesture recognition based on computer vision, including eye-gaze recognition, face recognition, head recognition, gesture recognition, and posture recognition. By rearranging development of the human machine interaction technique, it is concluded that ordinary human machine interface is double-sword in HM interaction.
At the same time,“Head-gesture-recognition based Virtual Library”was designed in order to study the techniques in every part of the computer-based gesture recognition. The advantages and disadvantages were analyzed while showing some novel ways of HM interaction.
By the ways of classifying, analyzing, experimenting ,designing and concluding, conclusion is drawn that the computer vision based recognition will help computers understand of the users’behavior, and free them out from restriction of mouse and keyboard, make interaction more naturally. What if the computer saw as the human did, will the artificial intelligence reach the level of understanding human. Then the HM interface will disappear ,taken place by the“Hidden HM Interaction”.
The study on this system ,which covers multiple subjects such as compute science, artificial intelligence, neuron science, bio-physics, cognition science, and artology, have great significance in exploring new ways of HM interaction and new techniques of robot design.
引文
1路凯,李小坚.手势识别研究概述.西安文理学院学报(自然科学版), 2006, (02):91~94
2 Bradski G,Yeo B L,Yeung M M. Gesture for video content navigation. Proceedings of the Storage and Retrieval for Imageand Video Databases VII, USA, 1999:230~242
3 Kervrann,C. A hierarchical Markov modeling approach for the segmentation and tracking of deformable shapes. Graphical Models and Image Processing, 1998,60(3):173~195
4 Gluckman J,Nayar S K. Planar catadioptric stereo: geometry and calibration. Proceedings of the Computer Vision and Pattern Recognition, USA, 1999:22~28
5路童芳.新媒体艺术.东南大学出版社, 2006:129 224 226 204
6 T. Darrell, B. Moghaddam, A. P. Pentland. Active face tracking and pose estimation in an interactive room. MIT Media Laboratory Perceptual Computing Group Technical Report, 1996:356
7 M. Suwa, N. Sugie, K. Fujimora. A preliminary note on pattern recognition of human emotional expression. Proceedings of the Fourth International Joint Conferenceon Pattern Recognition, Japan, 1978: 408~410
8 B. Fasel, J.Luettin. AutomaticfacialexpreSSion analysis: a survey,Pattern Recognition,2003,36(01):259~275
9刘伟锋.人脸表情识别研究.中国科学技术大学博士学位论文. 2007:2 8~9
10 S. Gong, S. McKenna, and J. Collins. An investigation into face pose distributions. IEEE International Conference on Automatic Face and Gesture Recognition, Vermont, 1996, USA:265~270
11 L. Brown, Y. Tian. A study of coarse head pose estimation. IEEE Workshop on Motion and Video Computing, Florida, 2002:125~130
12董力赓,陶霖密,徐光祐.头部姿态和动作的识别与理解.第三届和谐人机环境联合学术会议,山东大学, 2007:177
13 D. Knight, S. Bayoumi, S. Mills, A. Crabtree, S. Adolphs, T. Pridmore, R. Carter, Beyond the Text: Construction and Analysis of Multi-Modal Linguistic Corpora . Proceedings of the 2nd International Conference one-Social Science, Manchester, 2006:28~30
14 G. McGlaun, Robust Video-Based Recognition of Dynamic Head Gestures in Various Domains-Comparing a Rule-Based and a Stochastic Approach. 5th International Gesture Workshop on Gesture-Based Communication in Human-Computer Interaction, Genova, 2003, Italy: 15~17
15陈胜勇,刘盛.基于OpenCV的计算机视觉技术实现.科学出版社, 2008:1~6
16 Becker D A. Sensei: A real-time recognition, feedback and training system for T’ai Chi gestures. Cambridge: MIT Media Lab Perceptual Computing Group Technical Report No. 426, 1997:10~15
17 Davis J W, Bobick A F. The representation and recognition of action using temporal templates. Cambridge: MIT Media Lab Perceptual Computer Section, 1996
18 Takuichi Nishimura, Toshiro Mukai, Ryuichi Oka. Spotting recognition of gestures performed by people from a single time-varying image. Becker D A ed. Proceedings of IEEE/RSJ IROS’97. Cambridge: MIT Press,1997.967~972
19王兴伟,才国清,刘积仁,大西晟.一种基于运动区域的姿势识别方法.东北大学学报(自然科学版), 2001,22 (01):5~8
20黄飞跃,徐光祐.视角无关的动作识别.软件学报, 2008,19(07):1623~1633
21吴健康,肖锦玉.计算机视觉基本理论和方法.中国科学技术出版社, 1993:16~17
22程祥.人体动作识别的研究.电脑知识与技术(学术交流), 2006, (20) :121
23 David A Forsyth, Jean Ponce. Computer Vision: A Modern Approach.电子工业出版社, 2004:424~432.
24 http://www.siggraph.org/s97/conference/garden/morphin.html
25 S.Fujie, Y.Ejiri, K.Nakajima, Y.Matsusaka, T.Kobayashi. A conversation robot using head gesture recognition as para-linguistic information. Proceedings of 13th IEEE International Workshop on Robot and Human Communication, Roman, 2004:159~164
26 P.Jia and H.Hu. Head Gesture based Control of an Intelligent Wheelchair. The 11th Annual conference of Chinese Automation and Computing Society in the UK, Sheffield, UK, 2005:1~3
27孙晓明,陈一民,陈养彬,殷烨.基于视觉的动态手势识别.计算机工程与设计, 2005,26(11):2934~2936
28 C Hardenberg, F Berard. Bare-hand human-computer interaction. Proceedings of the ACM Workshop on Perceptive User Interfaces, New York, 2001. ACM Press:1~8
29 W T Freeman, K Tanaka. Computer vision for computer games. Proc Int’l Conf on Automatic Face and Gesture Recognition, 1996. IEEE Press:100~105.
30金连文,徐睿,杨端端,镇立新,黄建成.手指书写:一种虚拟文字识别人机交互新方法.电子学报, 2007,35(03):396~400
31 http://v.youku.com/v_show/id_XOTU2NTU0ODA=.html
32 http://www.cnbeta.com/articles/85715.htm
33李长山.虚拟现实技术及其应用.石油工业出版. 2006:66
34高小红,裴忠诚.人机界面的发展历程.水利电力机械, 2006, 28(02):64~65
35 Jef Raskin. The Humane Interface: New Directions for Designing Interactive Systems.史元春译.机械工业出版社. 2004:3~6
36 [德]奥利弗·格劳.虚拟艺术.陈玲主译.清华大学出版社. 2007:145~146
37赵文彬,张艳宁.角点检测技术综述.计算机应用研究, 2006,(10):17~19
38 C. Harris, M.J. Stephens. A combined corner and edge detector. InAlvey Vision Conference, 1988:147~152
39刘瑞祯,于仕琪. OpenCV教程(基础篇).北京航空航天大学出版社. 2007: 249
40 Bruce D. Lucas Takeo Kanade. An Iterative Image Registration Technique with an Application to Stereo Vision, Proceedings of the 7th International Joint Conference on Artificial Intelligence, Vancouver, 1981:674~679
41刘相滨,向坚持,王胜春.人行为识别与理解研究探讨.计算机与现代化, 2004, (12):4
42张毓晋,图像理解.第2版.清华大学出版社, 2007:P298
43 http://www.jswl.cn/course/psychology/illusion/hall/zollner/zollner.htm
44 Donald Hearn. Computer Graphics with OpenGL.第3版.电子工业出版社, 2004:3
45 http://hi.baidu.com/weiyisecailfw/album/item/dfd5dc08cad0419cd1581bdf.html
46 http://www.jswl.cn/course/psychology/illusion/hall/ambig/perceptual_ambiguity.html
47傅玉川,王植恒.视错觉现象研究.自然杂志. 1992, 15(05):348
48彭龄,张必隐.认知心理学.浙江教育出版社, 2004:105~106
49 [美]雷·库兹韦尔.灵魂机器的时代——当计算机超过人类智能时.沈志彦,祁阿红,王晓冬译.上海世纪出版集团, 2006:91~127
