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The modeling of human sensation in virtual environments.

Ka Keung Caramon Lee. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 100-105). / Abstracts in English and Chinese. / Contents --- p.iii / List of Figures --- p.vi / List of Tables --- p.ix / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Related Work --- p.3 / Chapter 1.2.1 --- Empirical Psychophysical Equations --- p.3 / Chapter 1.2.2 --- Industry Standards --- p.4 / Chapter 1.2.3 --- Fuzzy Logic --- p.4 / Chapter 1.2.4 --- Neural Networks --- p.5 / Chapter 1.3 --- Organization of Thesis --- p.7 / Chapter 2 --- Experimental Design --- p.9 / Chapter 2.1 --- Human Motion Sense --- p.9 / Chapter 2.2 --- Full-Body Motion Virtual Reality System --- p.12 / Chapter 2.3 --- Human Sensation Measure --- p.15 / Chapter 2.4 --- Trajectory Segmentation --- p.16 / Chapter 3 --- Learning and Validation of Human Sensation Models --- p.22 / Chapter 3.1 --- Cascade Neural Networks --- p.23 / Chapter 3.1.1 --- Dynamic Mapping --- p.26 / Chapter 3.2 --- Experimental Trajectory Data --- p.26 / Chapter 3.3 --- Effect of Trajectory Segmentation --- p.31 / Chapter 3.4 --- Model Validation --- p.32 / Chapter 3.5 --- Similarity Measure --- p.33 / Chapter 3.6 --- Similarity Measure Results --- p.38 / Chapter 4 --- Input Reduction for Human Sensation Modeling --- p.40 / Chapter 4.1 --- Introduction --- p.40 / Chapter 4.2 --- Input Reduction --- p.41 / Chapter 4.3 --- Feature Extraction and Input Selection --- p.42 / Chapter 4.4 --- Feature Extraction Using Principal Component Analysis --- p.44 / Chapter 4.5 --- Independent Component Analysis --- p.48 / Chapter 4.5.1 --- Measure of Gaussianity --- p.50 / Chapter 4.5.2 --- The Fixed Point ICA Algorithm --- p.51 / Chapter 4.6 --- Input Reduction Using Independent Component Analysis --- p.52 / Chapter 4.6.1 --- ICA Without Dimension Reduction --- p.52 / Chapter 4.6.2 --- Feature Extraction Using ICA --- p.55 / Chapter 4.6.3 --- Input Selection Using ICA --- p.57 / Chapter 4.6.4 --- Applying Input Selection by ICA on the Furnace Data --- p.58 / Chapter 4.6.5 --- Applying Input Selection by ICA to Sensation Modeling --- p.65 / Chapter 4.6.6 --- Cross Verification of Selected Inputs --- p.70 / Chapter 4.7 --- Summary on Input Reduction for Human Sensation Modeling --- p.72 / Chapter 5 --- Stimulus Modification Based on Human Sensation --- p.74 / Chapter 5.1 --- Need for Stimulus Modification --- p.74 / Chapter 5.2 --- Sensation Grades --- p.75 / Chapter 5.3 --- Trajectory Modification Scheme --- p.77 / Chapter 5.4 --- Experiments --- p.80 / Chapter 6 --- Conclusion --- p.86 / Chapter 6.1 --- Contributions --- p.86 / Chapter 6.2 --- Future Work --- p.87 / Chapter A --- Platform Model --- p.88 / Chapter A.1 --- Inverse Kinematics --- p.90 / Chapter A.2 --- Forward Kinematics --- p.93 / Chapter A.3 --- Platform Dynamics --- p.99 / Bibliography --- p.100

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_323241
Date January 2000
ContributorsLee, Ka Keung Caramon., Chinese University of Hong Kong Graduate School. Division of Mechanical and Automation Engineering.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography
Formatprint, x, 105 leaves : ill. ; 30 cm.
RightsUse 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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