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Modeling of moving object trajectory by spatio-temporal learning for abnormal behavior detection

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3 Author(s)
Hawook Jeong ; Perception & Intell. Lab., Seoul Nat. Univ., Seoul, South Korea ; Hyung Jin Chang ; Jin Young Choi

This paper proposes a trajectory analysis method by handling the spatio-temporal property of trajectory. Not using similarity measures of two trajectories, our model analyzes overall path of a trajectory. Learning of spatio property is presented as semantic regions (e.g. go straight, turn left, turn right) that are clustered effectively using topic model. The temporal order of observations on a trajectory is taken into account using HMM for detecting global anomaly. Results of experiments show that modeling of semantic region and detecting of unusual trajectories are successful even in complex scenes.

Published in:

Advanced Video and Signal-Based Surveillance (AVSS), 2011 8th IEEE International Conference on

Date of Conference:

Aug. 30 2011-Sept. 2 2011