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Proceedings Paper

Advanced vehicle tracking in persistent aerial surveillance video
Author(s): Jiangjian Xiao; Hui Cheng; Harpreet Sawhney
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Paper Abstract

This paper presents a relational graph based approach to track thousands of vehicles from persistent wide area airborne surveillance (WAAS) videos. Due to the low ground sampling distance and low frame rate, vehicles usually have small size and may travel a long distance between consecutive frames, WAAS videos pose great challenges to correct associate existing tracks with targets. In this paper, we explore road structure information to regulate both object based vertex matching and pair-wise edge matching schemes in a relational graph. The proposed relational graph approach then unifies these two matching schemes into a single cost minimization framework to produce a quadratic optimized association result. The experiments on hours of real WAAS videos demonstrate the relational graph matching framework effectively improves vehicle tracking performance in large scale dense traffic scenarios.

Paper Details

Date Published: 26 April 2010
PDF: 7 pages
Proc. SPIE 7668, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VII, 76680I (26 April 2010); doi: 10.1117/12.849519
Show Author Affiliations
Jiangjian Xiao, Sarnoff Corp. (United States)
Hui Cheng, Sarnoff Corp. (United States)
Harpreet Sawhney, Sarnoff Corp. (United States)


Published in SPIE Proceedings Vol. 7668:
Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VII
Daniel J. Henry, Editor(s)

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