Titlebook: Contextual Analysis of Videos; Myo Thida,How-lung Eng,Paolo Remagnino Book 2013 Springer Nature Switzerland AG 2013

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1559-8136 ptima interact frequently. A novel particle swarm optimization (PSO) algorithm that uses a set of multiple swarms is presented. Through particles and swarms div978-3-031-01121-4978-3-031-02249-4Series ISSN 1559-8136 Series E-ISSN 1559-8144

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Book 2013arget and multiple targets. Over the last few decades, computer vision researchers have been working to improve the accuracy and robustness of algorithms to analyse the context of a video automatically. In general, the research work in this area can be categorized into three major topics: 1) countin

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1559-8136 a single target and multiple targets. Over the last few decades, computer vision researchers have been working to improve the accuracy and robustness of algorithms to analyse the context of a video automatically. In general, the research work in this area can be categorized into three major topics:

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Valentí Rull,Teresa Vegas-Vilarrúbiaystems collect a huge amount of video data everyday, it is important to automate the process of video context analysis (Figure 1.1). Automating surveillance tasks such as intruder detection, people tracking, detection of abandoned luggage and abnormal behaviour is a desirable and interesting problem to solve.

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Tomasz Zurek,Jonathan Kwik,Tom van Engersindividual targets becomes more challenging. As a result, tracking-based approaches are inadequate for analysing the behaviours of a crowd. To address this limitation, in recent years, researchers have proposed to monitor the behaviour of a crowd without identifying the locations and actions of individuals participated in the crowd event.

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Tracking Multiple Targets Using Particle Swarm Optimisation,andard (PSO) algorithm and its variants for tracking targets in surveillance videos. The proposed method extends the standard PSO algorithm to the problem of finding dynamic optima (pedestrians) where these optima interact frequently.