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Real-time gesture recognition using MEMS acceleration sensors. / 基於MEMS加速度傳感器的人體姿勢實時識別系統 / Ji yu MEMS jia su du chuan gan qi de ren ti zi shi shi shi shi bie xi tong

by Zhou, Shengli. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 70-75). / Abstract also in Chinese. / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Background of Gesture Recognition --- p.1 / Chapter 1.2 --- HCI System --- p.2 / Chapter 1.2.1 --- Vision Based HCI System --- p.2 / Chapter 1.2.2 --- Accelerometer Based HCI System --- p.4 / Chapter 1.3 --- Pattern Recognition Methods --- p.6 / Chapter 1.4 --- Thesis Outline --- p.7 / Chapter Chapter 2 --- 2D Hand-Written Character Recognition --- p.8 / Chapter 2.1 --- Introduction to Accelerometer Based Hand-Written Character Recognition --- p.8 / Chapter 2.1.1 --- Character Recognition Based on Trajectory Reconstruction --- p.9 / Chapter 2.1.2 --- Character Recognition Based on Classification --- p.10 / Chapter 2.2 --- Neural Network --- p.11 / Chapter 2.2.1 --- Mathematical Model of Neural Network (NN) --- p.11 / Chapter 2.2.2 --- Types of Neural Network Learning --- p.13 / Chapter 2.2.3 --- Self-Organizing Maps (SOMs) --- p.14 / Chapter 2.2.4 --- Properties of Neural Network --- p.16 / Chapter 2.3 --- Experimental Setup --- p.17 / Chapter 2.4 --- Configuration of Sensing Mote --- p.18 / Chapter 2.5 --- Data Acquisition Methods --- p.19 / Chapter 2.6 --- Data Preprocessing Methods --- p.20 / Chapter 2.6.1 --- Fast Fourier Transform (FFT) --- p.21 / Chapter 2.6.2 --- Discrete Cosine Transform (DCT) --- p.23 / Chapter 2.6.3 --- Problem Analysis --- p.25 / Chapter 2.7 --- Hand-written Character Classification using SOMs --- p.26 / Chapter 2.7.1 --- Recognition of All Characters in the Same Group --- p.27 / Chapter 2.7.2 --- Recognize the Numbers and Letters Respectively --- p.28 / Chapter 2.8 --- Conclusion --- p.29 / Chapter Chapter 3 --- Human Gesture Recognition --- p.32 / Chapter 3.1 --- Introduction to Human Gesture Recognition --- p.32 / Chapter 3.1.1 --- Dynamic Gesture Recognition --- p.32 / Chapter 3.1.2 --- Hidden Markov Models (HMMs) --- p.33 / Chapter 3.1.2.1 --- Applications of HMMs --- p.34 / Chapter 3.1.2.2 --- Training Algorithm --- p.35 / Chapter 3.1.2.3 --- Recognition Algorithm --- p.35 / Chapter 3.2 --- System Architecture --- p.36 / Chapter 3.2.1 --- Experimental Devices --- p.36 / Chapter 3.2.2 --- Data Acquisition Methods --- p.38 / Chapter 3.2.3 --- System Work Flow --- p.39 / Chapter 3.3 --- Real-Time Gesture Spotting --- p.40 / Chapter 3.3.1 --- Introduction --- p.40 / Chapter 3.3.2 --- Gesture Segmentation Based on Standard Deviation Calculation --- p.42 / Chapter 3.3.3 --- Evaluation of Gesture Spotting Program --- p.47 / Chapter 3.4 --- Comparison of Data Processing Methods --- p.48 / Chapter 3.4.1 --- Discrete Cosine Transform (DCT) --- p.48 / Chapter 3.4.2 --- Discrete Wavelet Transform (DWT) --- p.49 / Chapter 3.4.3 --- Zero Bias Compensation and Filtering (ZBC&F) --- p.51 / Chapter 3.4.4 --- Comparison of Experimental Results --- p.52 / Chapter 3.5 --- Data Base Setup --- p.53 / Chapter 3.6 --- Experimental Results Based on the Database Obtained from Ten Test Subjects --- p.53 / Chapter 3.6.1 --- Experimental Results when Gestures are Manually and Automatically “cut´ح --- p.54 / Chapter 3.6.2 --- The Influence of Number of Dominant Frequencies on Recognition --- p.55 / Chapter 3.6.3 --- The Influence of Sampling Frequencies on Recognition --- p.59 / Chapter 3.6.4 --- Influence of Number of Test Subjects on Recognition --- p.62 / Chapter 3.6.4.1 --- Experimental Results When Training and Testing Subjects Are Overlaped --- p.61 / Chapter 3.6.4.2 --- Experimental Results When Training and Testing Subjects Are Not Overlap --- p.62 / Chapter 3.6.4.3 --- Discussion --- p.65 / Chapter Chapter 4 --- Conclusion --- p.68 / Bibliography --- p.70

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_326717
Date January 2009
ContributorsZhou, Shengli., 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, ix, 75 leaves : ill. (some col.) ; 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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