Mr. Michael Yonghua Zhang Profile

Michael Yonghua Zhang

at Univ of Calgary

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Proceedings Article | 16 January 2006 Paper

Subjective trajectory characterization: acquisition, matching, and retrieval

Michael Zhang, Luke Olsen, Jeffrey Boyd

Proceedings Volume 6061, 60610P (2006) https://doi.org/10.1117/12.642362

KEYWORDS: Particle filters, Databases, Detection and tracking algorithms, Particles, Shape analysis, Surveillance, Automatic tracking, Cameras, RGB color model, Video surveillance

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We describe a system that automatically tracks moving objects in a scene and subjectively characterizes the object trajectories for storage and retrieval. A multi-target color-histogram particle filter combined with besthypothesis data association is the foundation of our trajectory acquisition algorithm. To improve computational performance, we use quasi-Monte-Carlo methods to reduce the number of particles required by each filter. The tracking system operates in real-time to produce a stream of XML documents that contain the object trajectories. To characterize trajectories subjectively, we form a set of shape templates that describes basic maneuvers (e.g., gentle turn right, hard turn left, straight line). Procrustes shape analysis provides a scaleand rotation-invariant mechanism to identify occurrences of these maneuvers within a trajectory. To add spatial information to our trajectory representation, we partition the two-dimensional space under surveillance into a set of mutually exclusive regions. A temporal sequence of region-to-region transitions gives a spatial representation of the trajectory. The shape and position descriptions combine to form a compact, high-level representation of a trajectory. We provide similarity measures for the shape, position, and combined shape and position representations.

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