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Real-Time 3D Head Position Tracker System with Stereo

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Real-Time 3D Head Position Tracker System with Stereo REAL-TIME 3D HEAD POSITION TRACKER SYSTEM WITH STEREO CAMERAS USING A FACE RECOGNITION NEURAL NETWORK BY JAVIER IGNACIO GIRADO B. Electronics Engineering, ITBA University, Buenos Aires, Argentina, 1982 M. Electronics Engineering, ITBA University, Buenos Aires, Argentina 1984 THESIS Submitted as partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science in the Graduate College of the University of Illinois at Chicago, 2004 Chicago, Illinois ACKNOWLEDGMENTS I arrived at UIC in the winter of 1996, more than seven years ago. I had a lot to learn: how to find my way around a new school, a new city, a new country, a new culture and how to do computer science research. Those first years were very difficult for me and honestly I would not have made it if it were not for my old friends and the new ones I made at the laboratory and my colleagues. There are too many to list them all, so let me juts mention a few examples. I would like to thank my thesis committee (Thomas DeFanti, Daniel Sandin, Andrew Johnson, Jason Leigh and Joel Mambretti) for their unwavering support and assistance. They provided guidance in several areas that helped me accomplish my research goals and were very encouraging throughout the process. I would especially like to thank my thesis advisor Daniel Sandin for laying the foundation of this work and his continuous encouragement and feedback. He has been a constant source of great ideas and useful guidelines during my Thesis’ program. Thanks to Professor J. Ben-Arie for teaching me about science and computer vision. Thanks to Andy Johnson and Jason Leigh for keeping me in track, and expand my vision of sci-fi and anime. I would also like to recognize Maxine Brown and Laura Wolf who have provided me very helpful technical tips for organizing and writing several research documents, papers and this dissertation. Most at all, I would want to express my sincere gratitude to my friends, Laura Wolf, Brenda Lopez-Silva and Cristian Luciano for their help, both personally and professionally. JIG iii TABLE OF CONTENTS CHAPTER PAGE 1. INTRODUCTION.......................................................................................................................................1 1.1. BACKGROUND.........................................................................................................................................1 1.2. MOTIVATION ...........................................................................................................................................1 1.3. THE GOAL ...............................................................................................................................................2 1.4. ARTIFICIAL NEURAL NETWORKS .........................................................................................................3 1.5. THE CHALLENGE OF FACE DETECTION AND RECOGNITION.........................................................3 1.6. AN IMAGE-BASED APPROACH USING NEURAL NETWORKS ............................................................5 1.7. EVALUATION ...........................................................................................................................................8 2. BACKGROUND........................................................................................................................................17 2.1. INTRODUCTION.....................................................................................................................................17 2.2. BACKGROUND IN VR ...........................................................................................................................17 2.2.1. BRIEF INTRODUCTION OF VIRTUAL REALITY AND ITS DEVICES ........................................17 2.2.2. THE NEED AND IMPORTANCE OF TRACKER SYSTEMS IN VR..............................................18 2.3. BACKGROUND IN COMMERCIAL VR TRACKER DEVICES ...............................................................19 2.3.1. TRACKER SYSTEMS USED IN VR ENVIRONMENT ..................................................................19 2.3.2. DISADVANTAGES IN TRACKER SYSTEMS USED IN VR ENVIRONMENT ..............................23 2.3.3. REAL SPECIFICATION OF TRACKER SYSTEMS USED IN VR ENVIRONMENT .......................24 2.3.4. ADVANTAGES IN TRACKER SYSTEMS USED IN VR ENVIRONMENT.....................................26 3. PROPOSING NEW TRACKER SYSTEM...........................................................................................27 3.1. INTRODUCTION.....................................................................................................................................27 3.1.1. A WORD OF TRACKER LATENCY (OR LAG) .............................................................................27 3.1.2. WHAT IS A REAL-TIME SYSTEM?...............................................................................................29 3.2. DEFINING THE NEW TRACKER SYSTEMS SPECIFICATIONS............................................................30 3.3. SPECIFYING THE HARDWARE AND THE ENVIRONMENT................................................................32 3.4. THEORETICAL TRACKER SPECIFICAIONS USING VARRIERTM AUTOSTEREOSCOPIC DISPLAY AS A VR ENVIRONMENT ..............................................................................................................................36 4. DATA PREPARATION...........................................................................................................................41 4.1. INTRODUCTION.....................................................................................................................................41 4.2. PREPROCESSING FOR BRIGHTNESS AND CONTRAST ........................................................................41 4.2.1. STANDARD APPROACHES ...........................................................................................................41 4.2.2. THESIS APPROACH: GLOBAL EQUALIZATION IN A CONTROLLED ENVIRONMENT ..........44 4.2.3. THESIS APPROACH: GLOBAL PREPROCESSING USING SHADING CORRECTION................46 4.3. CAMERA CALIBRATION ........................................................................................................................51 5. HEAD TRACKER.....................................................................................................................................53 5.1. INTRODUCTION.....................................................................................................................................53 5.2. OVERVIEW OF TRACKING ALGORITHM .............................................................................................53 TRAINING......................................................................................................................................................71 5.2.1. METHODOLOGY DESCRIPTION.................................................................................................71 iv TABLE OF CONTENTS (continued) CHAPTER PAGE 5.2.2. ALGORITHM DESCRIPTION ........................................................................................................73 5.3. EVALUATION .........................................................................................................................................77 5.3.1. METHODOLOGY..........................................................................................................................77 5.3.2. TRACKER SYSTEM ERROR IN RECOGNIZER ONLY MODE....................................................78 5.3.3. TRACKER SYSTEM ERROR IN DETECTOR ONLY MODE........................................................79 5.3.4. TRACKER PERFORMANCE RATE ...............................................................................................81 5.3.5. FRAME RATE................................................................................................................................82 5.3.6. TRACKING LATENCY..................................................................................................................83 5.3.7. STATIC JITTER AND DRIFT.........................................................................................................85 5.3.8. DYNAMIC JITTER.........................................................................................................................85 5.3.9. STATIC PRECISION ......................................................................................................................86 5.3.10. RESOLUTION..............................................................................................................................87 6. REAL-TIME CAMERA-BASED FACE DETECTION USING A MODIFIED LAMSTAR NEURAL NETWORK SYSTEM................................................................................................................89 6.1. INTRODUCTION.....................................................................................................................................89 6.2. ORIGINAL FACE DETECTOR DESCRIPTION......................................................................................90 6.3. BACKGROUND.......................................................................................................................................91 6.4. SYSTEM OVERVIEW ..............................................................................................................................93 6.5. THE KOHONEN SELF-ORGANIZING-MAP........................................................................................93
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