A Vision-Based Approach for Human Hand Tracking and Gesture Recognition
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University of Windsor Scholarship at UWindsor Electronic Theses and Dissertations Theses, Dissertations, and Major Papers 2004 A vision-based approach for human hand tracking and gesture recognition. Jiangnan Lu University of Windsor Follow this and additional works at: https://scholar.uwindsor.ca/etd Recommended Citation Lu, Jiangnan, "A vision-based approach for human hand tracking and gesture recognition." (2004). Electronic Theses and Dissertations. 871. https://scholar.uwindsor.ca/etd/871 This online database contains the full-text of PhD dissertations and Masters’ theses of University of Windsor students from 1954 forward. These documents are made available for personal study and research purposes only, in accordance with the Canadian Copyright Act and the Creative Commons license—CC BY-NC-ND (Attribution, Non-Commercial, No Derivative Works). 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Master Thesis A Vision-Based Approach for Human Hand Tracking and Gesture Recognition Abstract Hand gesture interface has been becoming an active topic of human-computer interaction (HCI). The utilization of hand gestures in human-computer interface enables human operators to interact with computer environments in a natural and intuitive manner. In particular, bare hand interpretation technique frees users from cumbersome, but typically required devices in communication with computers, thus offering the ease and naturalness in HCI. Meanwhile, virtual assembly (VA) applies virtual reality (VR) techniques in mechanical assembly. It constructs computer tools to help product engineers planning, evaluating, optimizing, and verifying the assembly of mechanical systems without the need of physical objects. However, traditional devices such as keyboards and mice are no longer adequate due to their inefficiency in handling three-dimensional (3D) tasks. Special VR devices, such as data gloves, have been mandatory in VA. This thesis proposes a novel gesture-based interface for the application of VA. It develops a hybrid approach to incorporate an appearance-based hand localization technique with a skin tone filter in support of gesture recognition and hand tracking in the 3D space. With this interface, bare hands become a convenient substitution of special VR devices. Experiment results demonstrate the flexibility and robustness introduced by the proposed method to HCI. iii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Master Thesis A Vision-Based Approach for Human Hand Tracking and Gesture Recognition DEDICATED To my parents, my friends and all who love me and beloved iv Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Master Thesis A Vision-Based Approach for Human Hand Tracking and Gesture Recognition Acknowledgements I must begin by acknowledging my supervisor, Dr. Xiaobu Yuan, for sharing his wisdom and his experience while giving me constant advice throughout my study. I am also grateful to him for giving me the artistic freedom necessary to realize this task. I would like to extend my sincere appreciation to my committee members, Dr. Fritz Rieger and Dr. Christie Ezeife, for all their kind help, encouragement and guidance. My special thanks go to Yingxin Xia for her understanding and unbelievable supports. Finally, I would like to express thanks to all others who have helped me to overcome the many technical difficulties in preparing this thesis. v Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Master Thesis A Vision-Based Approach for Human Hand Tracking and Gesture Recognition Table of Contents ABSTRACT............................................................................................... iii DEDICATION........................................................................................... iv ACKNOWLEDGEMENT..........................................................................v LIST OF FIGURES..................................................................................vii 1. INTRODUCTION............................................................................... 1 1.1 Previous Work........................................................................................................ 2 1.1.1 Vision-Based Hand Gesture Interface Architecture ..........................................3 1.1.2 State-of-Art...................................................................................................... 4 1.2 Contributions.......................................................................................................... 6 1.3 Outline of Thesis.................................................................................................... 6 2. HAND GESTURE MODELING.........................................................8 2.1 Hand Gesture Definition ......................................................................................... 8 2.2 Gesture Categorization..........................................................................................10 2.3 3D-based Gesture Modeling ..................................................................................12 2.4 Appearance-based Gesture Modeling .................................................................... 13 3. GESTURE ANALYSIS FOR HAND LOCALIZATION................15 3.1 Color-based Gesture Analysis ...............................................................................15 3.1.1 Skin Color Histogram.....................................................................................16 3.1.2 Color Space........................... 17 3.1.3 Color space reduction and transformation.......................................................18 3.1.4 Limitations......................................................................................................18 3.2 Motion-based Gesture Analysis ............................................................................ 19 3.2.1 Image Differencing.........................................................................................19 3.2.2 Background Image Generation.......................................................................20 3.3 A Hybrid Model for Hand Localization................................................................21 4. 3D HAND POSITION TRACKING.................................................22 4.1 Feature Selection and Detection............................................................................22 4.1.1 Fingertips.......................................................................................................23 4.1.2 Silhouettes and Contours............................................................................... 23 4.1.3 3D-based Feature Estimation ..........................................................................24 4.2 Projective Geometry............................................................................................