Yu Ying-Kin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 108-116). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgements --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation and Objectives --- p.1 / Chapter 1.2 --- Problem Definition --- p.3 / Chapter 1.3 --- Contributions --- p.6 / Chapter 1.4 --- Related Publications --- p.8 / Chapter 1.5 --- Organization of the Paper --- p.9 / Chapter 2 --- Background --- p.11 / Chapter 2.1 --- Introduction --- p.11 / Chapter 2.2 --- Pose Estimation --- p.12 / Chapter 2.2.1 --- Overview --- p.12 / Chapter 2.2.2 --- Lowe's Method --- p.14 / Chapter 2.2.3 --- The Genetic Algorithm by Hati and Sen- gupta --- p.15 / Chapter 2.3 --- Structure and Motion --- p.17 / Chapter 2.3.1 --- Overview --- p.17 / Chapter 2.3.2 --- The Extended Lowe's Method --- p.20 / Chapter 2.3.3 --- The Extended Kalman Filter by Azarbaye- jani and Pentland --- p.23 / Chapter 3 --- Model-based Pose Tracking Using Genetic Algo- rithms --- p.27 / Chapter 3.1 --- Introduction --- p.27 / Chapter 3.2 --- Overview of the Algorithm --- p.28 / Chapter 3.3 --- Chromosome Encoding --- p.29 / Chapter 3.4 --- The Genetic Operators --- p.30 / Chapter 3.4.1 --- Mutation --- p.30 / Chapter 3.4.2 --- Crossover --- p.31 / Chapter 3.5 --- Fitness Evaluation --- p.31 / Chapter 3.6 --- The Roulette Wheel Proportionate Selection Scheme --- p.32 / Chapter 3.7 --- The Genetic Algorithm Parameters --- p.33 / Chapter 3.8 --- Experiments and Results --- p.34 / Chapter 3.8.1 --- Synthetic Data Experiments --- p.34 / Chapter 3.8.2 --- Real Scene Experiments --- p.38 / Chapter 4 --- Recursive 3D Structure Acquisition Based on Kalman Filtering --- p.42 / Chapter 4.1 --- Introduction --- p.42 / Chapter 4.2 --- Overview of the Algorithm --- p.43 / Chapter 4.2.1 --- Feature Extraction and Tracking --- p.44 / Chapter 4.2.2 --- Model Initialization --- p.44 / Chapter 4.2.3 --- Structure and Pose Updating --- p.45 / Chapter 4.3 --- Structure Updating --- p.46 / Chapter 4.4 --- Pose Estimation --- p.49 / Chapter 4.5 --- Handling of the Changeable Set of Feature Points --- p.52 / Chapter 4.6 --- Analytical Comparisons with Other Algorithms --- p.54 / Chapter 4.6.1 --- Comparisons with the Interleaved Bundle Adjustment Method --- p.54 / Chapter 4.6.2 --- Comparisons with the EKF by Azarbaye- jani and Pentland --- p.56 / Chapter 4.7 --- Experiments and Results --- p.57 / Chapter 4.7.1 --- Synthetic Data Experiments --- p.57 / Chapter 4.7.2 --- Real Scene Experiments --- p.58 / Chapter 5 --- Simultaneous Pose Tracking and Structure Acqui- sition Using the Interacting Multiple Model --- p.63 / Chapter 5.1 --- Introduction --- p.63 / Chapter 5.2 --- Overview of the Algorithm --- p.65 / Chapter 5.2.1 --- Feature Extraction and Tracking --- p.65 / Chapter 5.2.2 --- Model Initialization --- p.66 / Chapter 5.2.3 --- Structure and Pose Updating --- p.66 / Chapter 5.3 --- Pose Estimation --- p.67 / Chapter 5.3.1 --- The Interacting Multiple Model Algorithm --- p.67 / Chapter 5.3.2 --- Design of the Individual EKFs --- p.71 / Chapter 5.4 --- Structure Updating --- p.74 / Chapter 5.5 --- Handling of the Changeable Set of Feature Points --- p.76 / Chapter 5.6 --- Analytical Comparisons with Other EKF-Based Algorithms --- p.77 / Chapter 5.6.1 --- Computation Speed --- p.77 / Chapter 5.6.2 --- Accuracy of the Recovered Pose Sequences --- p.79 / Chapter 5.7 --- Experiments and Results --- p.80 / Chapter 5.7.1 --- Synthetic Data Experiments --- p.80 / Chapter 5.7.2 --- Real Scene Experiments --- p.80 / Chapter 6 --- Empirical Comparisons of the Structure and Mo- tion Algorithms --- p.87 / Chapter 6.1 --- Introduction --- p.87 / Chapter 6.2 --- Comparisons Using Synthetic Data --- p.88 / Chapter 6.2.1 --- Image Residual Errors --- p.88 / Chapter 6.2.2 --- Computation Efficiency --- p.89 / Chapter 6.2.3 --- Accuracy of Recovered Pose Sequences . . --- p.91 / Chapter 6.3 --- Comparisons Using Real Images --- p.92 / Chapter 6.4 --- Summary --- p.97 / Chapter 7 --- Future Work --- p.99 / Chapter 8 --- Conclusion --- p.101 / Chapter A --- Kalman Filtering --- p.103 / Bibliography --- p.107
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_324669 |
| Date | January 2004 |
| Contributors | Yu, Ying-Kin., 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, xvi, 116 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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