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Proceedings Paper

Scaling up multi-camera tracking for real-world deployment
Author(s): Yogesh Raja; Shaogang Gong
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Paper Abstract

A user-assisted multi-camera tracking system employing several key novel methodologies has previously been shown to be highly effective in assisting human users in tracking targets of interest through industry-standard i-LIDS multi-camera benchmark data.1 A prototype system was developed in order to test and evaluate the effectiveness of this approach. In this paper, we develop this system further in order to improve tracking accuracy and further facilitate scalability to arbitrary numbers of camera views across much larger spatial areas and different locations. Specifically, we describe the following three areas of improvement: (1) dynamic learning mechanisms apply user feedback in adapting internal models to improve performance over time; (2) modular design and hardware acceleration techniques are explored with a view to real-time performance, extensive configurability to leverage available hardware and scalability to larger datasets; and (3) re-design of the user interface for deployment as a secure asynchronous remote web-based service. We conduct an extensive evaluation of the system in terms of: (1) tracking performance; and (2) the speed of the system in computation and in usage over a network. We use a newly collected real-world dataset significantly more challenging than i-LIDS, which comprises six cameras covering two London Underground stations. We show that: (1) dynamic learning is effective; (2) the user-assisted paradigm retains its effectiveness with this significantly more challenging dataset; (3) large-scale deployment and real-time computation is feasible due to linear scalability; (4) context-aware user search strategies and external non-visual information can aid search convergence; and (5) storage and querying of meta-data is a bottleneck to be overcome.

Paper Details

Date Published: 30 October 2012
PDF: 15 pages
Proc. SPIE 8546, Optics and Photonics for Counterterrorism, Crime Fighting, and Defence VIII, 85460R (30 October 2012); doi: 10.1117/12.973760
Show Author Affiliations
Yogesh Raja, Vision Semantics Ltd. (United Kingdom)
Shaogang Gong, Vision Semantics Ltd. (United Kingdom)

Published in SPIE Proceedings Vol. 8546:
Optics and Photonics for Counterterrorism, Crime Fighting, and Defence VIII
Colin Lewis; Douglas Burgess, Editor(s)

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