Lee Kwok Wai. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 144-148). / Text in English; abstracts in English and Chinese. / Lee Kwok Wai. / Abstract --- p.i / 摘要 --- p.ii / Acknowledgements --- p.iii / Table of Content --- p.iv / List of Figures & Tables --- p.viii / Chapter Chapter 1 --- Introduction --- p.1 / Chapter Chapter 2 --- Motion Symmetry and its Application in Classification of Articulated Motions --- p.5 / Chapter 2.1 --- Introduction --- p.7 / Chapter 2.1.1 --- Motivation & Related Works --- p.7 / Chapter 2.1.2 --- Transformation Matrix for a Rigid Motion --- p.8 / Chapter 2.2 --- Review of Motion Estimation --- p.9 / Chapter 2.2.1 --- Motion Estimation & Motion Fields --- p.9 / Chapter 2.2.2 --- Motion Field Construction from Optical Flow --- p.10 / Chapter 2.2.3 --- Motion Field Construction from Image Matching --- p.12 / Chapter 2.3 --- Motion Symmetry --- p.13 / Chapter 2.3.1 --- Problem Definition --- p.13 / Chapter 2.3.2 --- Definitions of Transformation Symmetry & Anti- symmetry --- p.14 / Chapter 2.3.2.1 --- Translation Symmetry --- p.15 / Chapter 2.3.2.2 --- Translation Anti-symmetry --- p.16 / Chapter 2.3.2.3 --- Rotation Symmetry --- p.17 / Chapter 2.3.2.4 --- Rotation Anti-symmetry --- p.18 / Chapter 2.3.2.5 --- Scaling Symmetry … --- p.18 / Chapter 2.3.2.6 --- Scaling Anti-symmetry --- p.19 / Chapter 2.3.3 --- Transformation Quasi-symmetry & Quasi-anti- symmetry --- p.19 / Chapter 2.3.4 --- Symmetric Transform of a Transformation --- p.19 / Chapter 2.3.5 --- Symmetric Motions & Periodic Symmetric Motions --- p.20 / Chapter 2.3.6 --- Transformation Vector Fields of Symmetric Motions --- p.20 / Chapter 2.4 --- Detection of Motion Symmetry --- p.23 / Chapter 2.4.1 --- Model-based Motion Parameter Analysis --- p.24 / Chapter 2.4.2 --- Transformation Matrices Analysis --- p.25 / Chapter 2.4.3 --- Simultaneous Resultant Transformation Matrix Analysis --- p.31 / Chapter 2.4.4 --- Motion Symmetry as a Continuous Feature --- p.38 / Chapter 2.5 --- Illustrations & Results … --- p.39 / Chapter 2.5.1 --- Experiment 1: Randomly Generated Data --- p.39 / Chapter 2.5.2 --- Experiment 2: Symmetry Axis for a 3D object --- p.41 / Chapter 2.6 --- Summary & Discussion --- p.44 / Chapter 2.7 --- Appendices --- p.47 / Chapter 2.7.1 --- Appendix 1: Reflection of a Point about a Line --- p.47 / Chapter 2.7.2 --- Appendix 2: Symmetric Transform of a Transformation --- p.49 / Chapter Chapter 3 --- Motion Representation by Feedforward Neural Networks --- p.53 / Chapter 3.1 --- Introduction --- p.54 / Chapter 3.2 --- Motion Modeling in Animation --- p.57 / Chapter 3.2.1 --- Parameterized Motion Representation --- p.58 / Chapter 3.2.2 --- Problems of Motion Analysis --- p.62 / Chapter 3.3 --- Multi-value Regression by Feedforward Neural Networks --- p.66 / Chapter 3.3.1 --- Review of Multi-value Regression Methods --- p.66 / Chapter 3.3.2 --- Problem Definition --- p.68 / Chapter 3.3.3 --- Proposed Methods --- p.69 / Chapter 3.3.3.1 --- Modular Networks with Verification Module --- p.69 / Chapter (a) --- Validation by Decoding --- p.70 / Chapter (b) --- Validation by inverse mapping --- p.71 / Chapter 3.3.3.2 --- Partition Algorithm --- p.73 / Chapter 3.4 --- Illustration & Results --- p.76 / Chapter 3.4.1 --- Cylindrical Spiral Function --- p.76 / Chapter 3.4.2 --- Elongated Cylindrical Spiral Function --- p.79 / Chapter 3.4.3 --- Cylindrical Spiral Surface --- p.83 / Chapter 3.4.4 --- S-curve Data --- p.87 / Chapter 3.4.5 --- Inverse Sine function --- p.89 / Chapter 3.5 --- Motion Analysis … --- p.91 / Chapter 3.6 --- Summary & Discussion --- p.94 / Chapter Chapter 4 --- Motion Representation by Recurrent Neural Networks --- p.98 / Chapter 4.1 --- Introduction --- p.99 / Chapter 4.1.1 --- Recurrent Neural Networks (RNNs) --- p.99 / Chapter 4.1.2 --- Fully & Partially Recurrent Neural Networks --- p.101 / Chapter 4.1.3 --- Back-propagation Training Algorithm --- p.105 / Chapter 4.2 --- Sequence Encoding by Recurrent Neural Networks --- p.106 / Chapter 4.2.1 --- Random Binary Sequence --- p.107 / Chapter 4.2.2 --- Angular Positions of Clock Needles --- p.108 / Chapter 4.2.3 --- Absolute Positions of Clock Needles´ةTips --- p.109 / Chapter 4.2.4 --- Henon Time Series --- p.111 / Chapter 4.2.5 --- Ikeda Time Series … --- p.112 / Chapter 4.2.6 --- Single-Input-Single-Output (SISO) Non-linear System --- p.114 / Chapter 4.2.7 --- Circular Trajectory --- p.115 / Chapter 4.2.8 --- Number Trajectories --- p.118 / Chapter 4.3 --- Animation Generation by Recurrent Neural Networks --- p.123 / Chapter 4.3.1 --- Storage & Generation of Animations --- p.127 / Chapter 4.3.2 --- Interpolation between two Motion Segments --- p.127 / Chapter 4.4 --- Motion Analysis by Recurrent Neural Networks --- p.129 / Chapter 4.5 --- Experimental Results --- p.130 / Chapter 4.5.1 --- Network Training --- p.130 / Chapter 4.5.2 --- Motion Interpolation --- p.134 / Chapter 4.5.3 --- Motion Recognition --- p.135 / Chapter 4.6 --- Summary & Discussion --- p.138 / Chapter Chapter 5 --- Conclusion --- p.141 / References --- p.144
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_323443 |
| Date | January 2001 |
| Contributors | Lee, Kwok Wai., Chinese University of Hong Kong Graduate School. Division of Electronic Engineering. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, bibliography |
| Format | print, xvi, 148 leaves : ill. ; 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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