Yu, Tsz Ho. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 95-100). / Abstract also in Chinese. / Chapter 1 --- Introduction --- p.2 / Chapter 1.1 --- Surveillance and Computer Vision --- p.3 / Chapter 1.2 --- The Need for Abnormal Behavior Detection --- p.3 / Chapter 1.2.1 --- The Motivation --- p.3 / Chapter 1.2.2 --- Choosing the Right Surveillance Target --- p.5 / Chapter 1.3 --- Abnormal Behavior Detection: An Overview --- p.6 / Chapter 1.3.1 --- Challenges in Detecting Abnormal Behaviors --- p.6 / Chapter 1.3.2 --- Limitations of Existing Approaches --- p.8 / Chapter 1.3.3 --- New Design Concepts --- p.9 / Chapter 1.3.4 --- Requirements for Abnormal Behavior Detection --- p.10 / Chapter 1.4 --- Contributions --- p.11 / Chapter 1.4.1 --- An Unsupervised Experience-based Approach for Abnormal Behavior Detection --- p.11 / Chapter 1.4.2 --- Motion Histogram Transform: A Novel Feature Descriptors --- p.12 / Chapter 1.4.3 --- Real-time Algorithm for Abnormal Behavior Detection --- p.12 / Chapter 1.5 --- Thesis Organization --- p.13 / Chapter 2 --- Literature Review --- p.14 / Chapter 2.1 --- From Segmentation to Visual Tracking --- p.14 / Chapter 2.1.1 --- Environment Modeling and Segmentation --- p.15 / Chapter 2.1.2 --- Spatial-temporal Feature Extraction --- p.18 / Chapter 2.2 --- Detecting Irregularities in Videos --- p.21 / Chapter 2.2.1 --- Model-based Method --- p.22 / Chapter 2.2.2 --- Non Model-based Method --- p.26 / Chapter 3 --- Design Framework --- p.29 / Chapter 3.1 --- Dynamic Scene and Behavior Model --- p.30 / Chapter 3.1.1 --- Images Sequences and Video --- p.30 / Chapter 3.1.2 --- Motions and Behaviors in Video --- p.31 / Chapter 3.1.3 --- Discovering Abnormal Behavior --- p.32 / Chapter 3.1.4 --- Problem Definition --- p.33 / Chapter 3.1.5 --- System Assumption --- p.34 / Chapter 3.2 --- Methodology --- p.35 / Chapter 3.2.1 --- Potential Improvements --- p.35 / Chapter 3.2.2 --- The Design Framework --- p.36 / Chapter 4 --- Implementation --- p.40 / Chapter 4.1 --- Preprocessing --- p.40 / Chapter 4.1.1 --- Data Input --- p.41 / Chapter 4.1.2 --- Motion Detection --- p.41 / Chapter 4.1.3 --- The Gaussian Mixture Background Model --- p.43 / Chapter 4.2 --- Feature Extraction --- p.46 / Chapter 4.2.1 --- Optical Flow Estimation --- p.47 / Chapter 4.2.2 --- Motion Histogram Transforms --- p.53 / Chapter 4.3 --- Feedback Learning --- p.56 / Chapter 4.3.1 --- The Observation Matrix --- p.58 / Chapter 4.3.2 --- Eigenspace Transformation --- p.58 / Chapter 4.3.3 --- Self-adaptive Update Scheme --- p.61 / Chapter 4.3.4 --- Summary --- p.62 / Chapter 4.4 --- Classification --- p.63 / Chapter 4.4.1 --- Detecting Abnormal Behavior via Statistical Saliencies --- p.64 / Chapter 4.4.2 --- Determining Feedback --- p.65 / Chapter 4.5 --- Localization and Output --- p.66 / Chapter 4.6 --- Conclusion --- p.69 / Chapter 5 --- Experiments --- p.71 / Chapter 5.1 --- Experiment Setup --- p.72 / Chapter 5.2 --- A Summary of Experiments --- p.74 / Chapter 5.3 --- Experiment Results: Part 1 --- p.78 / Chapter 5.4 --- Experiment Results: Part 2 --- p.81 / Chapter 5.5 --- Experiment Results: Part 3 --- p.83 / Chapter 5.6 --- Experiment Results: Part 4 --- p.86 / Chapter 5.7 --- Analysis and Conclusion --- p.86 / Chapter 6 --- Conclusions --- p.88 / Chapter 6.1 --- Application Extensions --- p.88 / Chapter 6.2 --- Limitations --- p.89 / Chapter 6.2.1 --- Surveillance Range --- p.89 / Chapter 6.2.2 --- Preparation Time for the System --- p.89 / Chapter 6.2.3 --- Calibration of Background Model --- p.90 / Chapter 6.2.4 --- Instability of Optical Flow Feature Extraction --- p.91 / Chapter 6.2.5 --- Lack of 3D information --- p.91 / Chapter 6.2.6 --- Dealing with Complex Behavior Patterns --- p.92 / Chapter 6.2.7 --- Potential Improvements --- p.92 / Chapter 6.2.8 --- New Method for Classification --- p.93 / Chapter 6.2.9 --- Introduction of Dynamic Texture as a Feature --- p.93 / Chapter 6.2.10 --- Using Multiple-camera System --- p.93 / Chapter 6.3 --- Summary --- p.94 / Bibliography --- p.95
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_326805 |
| Date | January 2009 |
| Contributors | Yu, Tsz Ho., 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, xiii, 100 leaves : ill. (chiefly 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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