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Machine Learning Methods for Behaviour Analysis and Anomaly Detection in Video by Olga Isupova is a nonfiction available to read on EtoBox.

What is Machine Learning Methods for Behaviour Analysis and Anomaly Detection in Video about?

This thesis proposes machine learning methods for understanding scenes via behaviour analysis and online anomaly detection in video. The book introduces novel Bayesian topic models for detection of events that are different from typical activities and a novel framework for change point detection for identifying sudden behavioural changes. Behaviour analysis and anomaly detection are key components of intelligent vision systems. Anomaly detection can be considered from two perspectives: abnormal events can be defined as those that violate typical activities or as a sudden change in behaviour. Topic modelling and change-point detection methodologies, respectively, are employed to achieve these objectives. The thesis starts with the development of learning algorithms for a dynamic topic model, which extract topics that represent typical activities of a scene. These typical activities are used in a normality measure in anomaly detection decision-making. The book also proposes a novel anomaly localisation procedure. In the first topic model presented, a number of topics should be specified in advance. A novel dynamic nonparametric hierarchical Dirichlet process topic model is then devel

Who reads Machine Learning Methods for Behaviour Analysis and Anomaly Detection in Video?

Author

Olga Isupova

Publisher

Springer International Publishing : Imprint: Springer

Published

2018

Language

EN

ISBN

9783319755076

Category

nonfiction

Subjects

Computer Science, Engineering, Science