Cheung, Lap Chi. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 91-95). / Abstracts in English and Chinese. / Chapter 1. --- INTRODUCTION --- p.1 / Chapter 1.1. --- Background --- p.1 / Chapter 1.1.1. --- Introduction to Intelligent Vehicle --- p.1 / Chapter 1.1.2. --- Typical Vehicle Tracking Systems for Rear-end Collision Avoidance --- p.2 / Chapter 1.1.3. --- Passive VS Active Vehicle Tracking --- p.3 / Chapter 1.1.4. --- Vision-based Vehicle Tracking Systems --- p.4 / Chapter 1.1.5. --- Characteristics of Computing Devices on Vehicles --- p.5 / Chapter 1.2. --- Motivation and Objectives --- p.6 / Chapter 1.3. --- Major Contributions --- p.7 / Chapter 1.3.1. --- A 3-phase Vision-based Vehicle Tracking Framework --- p.7 / Chapter 1.3.2. --- Camera-to-vehicle Distance Measurement by Single Camera --- p.9 / Chapter 1.3.3. --- Real Time Vehicle Detection --- p.10 / Chapter 1.3.4. --- Real Time Vehicle Tracking using Simplified Image Alignment --- p.10 / Chapter 1.4. --- Evaluation Platform --- p.11 / Chapter 1.5. --- Thesis Organization --- p.11 / Chapter 2. --- RELATED WORK --- p.13 / Chapter 2.1. --- Stereo-based Vehicle Tracking --- p.13 / Chapter 2.2. --- Motion-based Vehicle Tracking --- p.16 / Chapter 2.3. --- Knowledge-based Vehicle Tracking --- p.18 / Chapter 2.4. --- Commercial Systems --- p.19 / Chapter 3. --- 3-PHASE VISION-BASED VEHICLE TRACKING FRAMEWORK --- p.22 / Chapter 3.1. --- Introduction to the 3-phase Framework --- p.22 / Chapter 3.2. --- Vehicle Detection --- p.23 / Chapter 3.2.1. --- Overview of Vehicle Detection --- p.23 / Chapter 3.2.2. --- Locating the Vehicle Center - Symmetrical Measurement --- p.25 / Chapter 3.2.3. --- Locating the Vehicle Roof and Bottom --- p.28 / Chapter 3.2.4. --- Locating the Vehicle Sides - Over-complete Haar Transform --- p.30 / Chapter 3.3. --- Vehicle Template Tracking Image Alignment --- p.37 / Chapter 3.3.5. --- Overview of Vehicle Template Tracking --- p.37 / Chapter 3.3.6. --- Goal of Image Alignment --- p.41 / Chapter 3.3.7. --- Alternative Image Alignment - Compositional Image Alignment --- p.42 / Chapter 3.3.8. --- Efficient Image Alignment - Inverse Compositional Algorithm --- p.43 / Chapter 3.4. --- Vehicle Template Update --- p.46 / Chapter 3.4.1. --- Situation of Vehicle lost --- p.46 / Chapter 3.4.2. --- Template Filling by Updating the positions of Vehicle Features --- p.48 / Chapter 3.5. --- Experiments and Discussions --- p.49 / Chapter 3.5. 1. --- Experiment Setup --- p.49 / Chapter 3.5.2. --- Successful Tracking Percentage --- p.50 / Chapter 3.6. --- Comparing with other tracking methodologies --- p.52 / Chapter 3.6.1. --- 1-phase Vision-based Vehicle Tracking --- p.52 / Chapter 3.6.2. --- Image Correlation --- p.54 / Chapter 3.6.3. --- Continuously Adaptive Mean Shift --- p.58 / Chapter 4. --- CAMERA TO-VEHICLE DISTANCE MEASUREMENT BY SINGLE CAMERA --- p.61 / Chapter 4.1 --- The Principle of Law of Perspective --- p.61 / Chapter 4.2. --- Distance Measurement by Single Camera --- p.62 / Chapter 5. --- REAL TIME VEHICLE DETECTION --- p.66 / Chapter 5.1. --- Introduction --- p.66 / Chapter 5.2. --- Timing Analysis of Vehicle Detection --- p.66 / Chapter 5.3. --- Symmetrical Measurement Optimization --- p.67 / Chapter 5.3.1. --- Diminished Gradient Image for Symmetrical Measurement --- p.67 / Chapter 5.3.2. --- Replacing Division by Multiplication Operations --- p.71 / Chapter 5.4. --- Over-complete Haar Transform Optimization --- p.73 / Chapter 5.4.1. --- Characteristics of Over-complete Haar Transform --- p.75 / Chapter 5.4.2. --- Pre-compntation of Haar block --- p.74 / Chapter 5.5. --- Summary --- p.77 / Chapter 6. --- REAL TIME VEHICLE TRACKING USING SIMPLIFIED IMAGE ALIGNMENT --- p.78 / Chapter 6.1. --- Introduction --- p.78 / Chapter 6.2. --- Timing Analysis of Original Image Alignment --- p.78 / Chapter 6.3. --- Simplified Image Alignment --- p.80 / Chapter 6.3.1. --- Reducing the Number of Parameters in Affine Transformation --- p.80 / Chapter 6.3.2. --- Size Reduction of Image A ligmnent Matrixes --- p.85 / Chapter 6.4. --- Experiments and Discussions --- p.85 / Chapter 6.4.1. --- Successful Tracking Percentage --- p.86 / Chapter 6.4.2. --- Timing Improvement --- p.87 / Chapter 7. --- CONCLUSIONS --- p.89 / Chapter 8. --- BIBLIOGRAPHY --- p.91
Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_326066 |
Date | January 2007 |
Contributors | Cheung, Lap Chi., Chinese University of Hong Kong Graduate School. Division of Computer Science and Engineering. |
Source Sets | The Chinese University of Hong Kong |
Language | English, Chinese |
Detected Language | English |
Type | Text, bibliography |
Format | print, xi, 95 leaves : ill. (some col.) ; 30 cm. |
Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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