Detecting irregularity in videos using spatiotemporal volumes.

• Other Authors: Li, Yun.
• Format: Others
• Language: English; Chinese
• Published: 2007
• Subjects: Computer vision > Mathematical models; Human activity recognition
• Online Access: http://library.cuhk.edu.hk/record=b5893341; http://repository.lib.cuhk.edu.hk/en/item/cuhk-326016

Li, Yun. === Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. === Includes bibliographical references (leaves 68-72). === Abstracts in English and Chinese. === Abstract --- p.I === 摘要 --- p.III === Acknowledgments --- p.IV === List of Contents --- p.VI === List of Figures --- p.VII === Chapter Chapter 1 --- Introduction --- p.1 === Chapter 1.1 --- Visual Detection --- p.2 === Chapter 1.2 --- Irregularity Detection --- p.4 === Chapter Chapter 2 --- System Overview --- p.7 === Chapter 2.1 --- Definition of Irregularity --- p.7 === Chapter 2.2 --- Contributions --- p.8 === Chapter 2.3 --- Review of previous work --- p.9 === Chapter 2.3.1 --- Model-based Methods --- p.9 === Chapter 2.3.2 --- Statistical Methods --- p.11 === Chapter 2.4 --- System Outline --- p.14 === Chapter Chapter 3 --- Background Subtraction --- p.16 === Chapter 3.1 --- Related Work --- p.17 === Chapter 3.2 --- Adaptive Mixture Model --- p.18 === Chapter 3.2.1 --- Online Model Update --- p.20 === Chapter 3.2.2 --- Background Model Estimation --- p.22 === Chapter 3.2.3 --- Foreground Segmentation --- p.24 === Chapter Chapter 4 --- Feature Extraction --- p.28 === Chapter 4.1 --- Various Feature Descriptors --- p.29 === Chapter 4.2 --- Histogram of Oriented Gradients --- p.30 === Chapter 4.2.1 --- Feature Descriptor --- p.31 === Chapter 4.2.2 --- Feature Merits --- p.33 === Chapter 4.3 --- Subspace Analysis --- p.35 === Chapter 4.3.1 --- Principal Component Analysis --- p.35 === Chapter 4.3.2 --- Subspace Projection --- p.37 === Chapter Chapter 5 --- Bayesian Probabilistic Inference --- p.39 === Chapter 5.1 --- Estimation of PDFs --- p.40 === Chapter 5.1.1 --- K-Means Clustering --- p.40 === Chapter 5.1.2 --- Kernel Density Estimation --- p.42 === Chapter 5.2 --- MAP Estimation --- p.44 === Chapter 5.2.1 --- ML Estimation & MAP Estimation --- p.44 === Chapter 5.2.2 --- Detection through MAP --- p.46 === Chapter 5.3 --- Efficient Implementation --- p.47 === Chapter 5.3.1 --- K-D Trees --- p.48 === Chapter 5.3.2 --- Nearest Neighbor (NN) Algorithm --- p.49 === Chapter Chapter 6 --- Experiments and Conclusion --- p.51 === Chapter 6.1 --- Experiments --- p.51 === Chapter 6.1.1 --- Outdoor Video Surveillance - Exp. 1 --- p.52 === Chapter 6.1.2 --- Outdoor Video Surveillance - Exp. 2 --- p.54 === Chapter 6.1.3 --- Outdoor Video Surveillance - Exp. 3 --- p.56 === Chapter 6.1.4 --- Classroom Monitoring - Exp.4 --- p.61 === Chapter 6.2 --- Algorithm Evaluation --- p.64 === Chapter 6.3 --- Conclusion --- p.66 === Bibliography --- p.68