Self-localization in urban environment via mobile imaging facility.

• Other Authors: Chim, Ho Ming.
• Format: Others
• Language: English; Chinese
• Published: 2008
• Subjects: Image registration; Image processing; Three-dimensional imaging; Location-based services
• Online Access: http://library.cuhk.edu.hk/record=b5893585; http://repository.lib.cuhk.edu.hk/en/item/cuhk-326366

Chim, Ho Ming. === Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. === Includes bibliographical references (leaves 58-62). === Abstracts in English and Chinese. === Acknowledgements --- p.i === Abstract --- p.ii === Chapter 1 --- Introduction --- p.1 === Chapter 1.1 --- Objectives --- p.1 === Chapter 1.2 --- Motivations --- p.1 === Chapter 1.3 --- Problem Statement --- p.2 === Chapter 1.4 --- Camera Self-Localization Approaches --- p.3 === Chapter 1.4.1 --- Based on Calibration Patterns --- p.3 === Chapter 1.4.2 --- Based on Self-calibration --- p.3 === Chapter 1.4.3 --- Based on Shape and Motion --- p.4 === Chapter 1.4.4 --- The Proposed Approach - Based on Junctions --- p.5 === Chapter 1.5 --- Thesis Organization --- p.6 === Chapter 2 --- Previous Work --- p.7 === Chapter 2.1 --- Camera Self-Localization --- p.7 === Chapter 2.1.1 --- Parallel Plane Features --- p.7 === Chapter 2.1.2 --- Parallelepiped Features --- p.8 === Chapter 2.1.3 --- Single View Geometric Features --- p.8 === Chapter 2.1.4 --- Shape and Motion --- p.8 === Chapter 2.1.5 --- Other Estimation Methods --- p.9 === Chapter 2.2 --- Feature Correspondences Establishment --- p.9 === Chapter 2.2.1 --- Feature-based Object Recognition --- p.9 === Chapter 2.2.2 --- Model-based Object Recognition --- p.10 === Chapter 3 --- Preliminaries --- p.11 === Chapter 3.1 --- Perspective Camera Model --- p.11 === Chapter 3.2 --- Camera Pose from Point Correspondences --- p.15 === Chapter 3.3 --- Camera Pose from Direction Correspondences --- p.16 === Chapter 4 --- A Junction-based Approach --- p.18 === Chapter 4.1 --- Use of Junction Correspondences for Determining Camera Pose --- p.18 === Chapter 4.1.1 --- Constraints from Point Information --- p.19 === Chapter 4.1.2 --- Constraint from Direction Information --- p.21 === Chapter 4.1.3 --- Junction Triplet Correspondences --- p.22 === Chapter 4.2 --- Extraction of Junctions and Junction Triplets from Image --- p.24 === Chapter 4.2.1 --- Handling Image Data --- p.24 === Chapter 4.2.2 --- Bridging Lines --- p.25 === Chapter 4.2.3 --- """L""-junctions" --- p.26 === Chapter 4.2.4 --- """Y"" and ""Adjunctions" --- p.27 === Chapter 4.2.5 --- Junction Triplets --- p.28 === Chapter 4.3 --- Establishment of the First Junction Triplet Correspondence --- p.30 === Chapter 4.3.1 --- Ordered Junction Triplets from Model --- p.30 === Chapter 4.3.2 --- A Junction Hashing Scheme --- p.31 === Chapter 4.4 --- Establishment of Points Correspondence --- p.33 === Chapter 4.4.1 --- Viewing Sphere Tessellation --- p.33 === Chapter 4.4.2 --- Model Views Synthesizing --- p.35 === Chapter 4.4.3 --- Affine Coordinates Computation --- p.35 === Chapter 4.4.4 --- Hash Table Filling --- p.38 === Chapter 4.4.5 --- Hash Table Voting --- p.38 === Chapter 4.4.6 --- Hypothesis and Confirmation --- p.39 === Chapter 4.4.7 --- An Example of Geometric Hashing --- p.40 === Chapter 5 --- Experimental Results --- p.43 === Chapter 5.1 --- Results from Synthetic Image Data --- p.43 === Chapter 5.2 --- Results from Real Image Data --- p.45 === Chapter 5.2.1 --- Results on Laboratory Scenes --- p.46 === Chapter 5.2.2 --- Results on Outdoor Scenes --- p.48 === Chapter 6 --- Conclusion --- p.51 === Chapter 6.1 --- Contributions --- p.51 === Chapter 6.2 --- Advantages --- p.52 === Chapter 6.3 --- Summary and Future Work --- p.52 === Chapter A --- Least-Squares Method --- p.54 === Chapter B --- RQ Decomposition --- p.56 === Bibliography --- p.58