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

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... 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.