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2008

A Survey of Vision-Based Trajectory Learning and Analysis for Surveillance

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A Survey of Vision-Based Trajectory Learning and Analysis for Surveillance
Abstract--This paper presents a survey of trajectory-based activity analysis for visual surveillance. It describes techniques that use trajectory data to define a general set of activities that are applicable to a wide range of scenes and environments. Events of interest are detected by building a generic topographical scene description from underlying motion structure as observed over time. The scene topology is automatically learned and is distinguished by points of interest and motion characterized by activity paths. The methods we review are intended for real-time surveillance through definition of a diverse set of events for further analysis triggering, including virtual fencing, speed profiling, behavior classification, anomaly detection, and object interaction.
Brendan Tran Morris, Mohan M. Trivedi
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2008
Where TCSV
Authors Brendan Tran Morris, Mohan M. Trivedi
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