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Proceedings Paper

Subjective trajectory characterization: acquisition, matching, and retrieval
Author(s): Michael Yonghua Zhang; Luke Olsen; Jeffrey E. Boyd
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Paper Abstract

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.

Paper Details

Date Published: 16 January 2006
PDF: 12 pages
Proc. SPIE 6061, Internet Imaging VII, 60610P (16 January 2006); doi: 10.1117/12.642362
Show Author Affiliations
Michael Yonghua Zhang, Univ. of Calgary (Canada)
Luke Olsen, Univ. of Calgary (Canada)
Jeffrey E. Boyd, Univ. of Calgary (Canada)

Published in SPIE Proceedings Vol. 6061:
Internet Imaging VII
Simone Santini; Raimondo Schettini; Theo Gevers, Editor(s)

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