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Proceedings Paper

Aerial video and ladar imagery fusion for persistent urban vehicle tracking
Author(s): Peter Cho; Daniel Greisokh; Hyrum Anderson; Jessica Sandland; Robert Knowlton
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Paper Abstract

We assess the impact of supplementing two-dimensional video with three-dimensional geometry for persistent vehicle tracking in complex urban environments. Using recent video data collected over a city with minimal terrain content, we first quantify erroneous sources of automated tracking termination and identify those which could be ameliorated by detailed height maps. They include imagery misregistration, roadway occlusion and vehicle deceleration. We next develop mathematical models to analyze the tracking value of spatial geometry knowledge in general and high resolution ladar imagery in particular. Simulation results demonstrate how 3D information could eliminate large numbers of false tracks passing through impenetrable structures. Spurious track rejection would permit Kalman filter coasting times to be significantly increased. Track lifetimes for vehicles occluded by trees and buildings as well as for cars slowing down at corners and intersections could consequently be prolonged. We find high resolution 3D imagery can ideally yield an 83% reduction in the rate of automated tracking failure.

Paper Details

Date Published: 10 May 2007
PDF: 12 pages
Proc. SPIE 6567, Signal Processing, Sensor Fusion, and Target Recognition XVI, 65670Z (10 May 2007); doi: 10.1117/12.718688
Show Author Affiliations
Peter Cho, MIT Lincoln Lab. (United States)
Daniel Greisokh, MIT Lincoln Lab. (United States)
Hyrum Anderson, MIT Lincoln Lab. (United States)
Jessica Sandland, MIT Lincoln Lab. (United States)
Robert Knowlton, MIT Lincoln Lab. (United States)

Published in SPIE Proceedings Vol. 6567:
Signal Processing, Sensor Fusion, and Target Recognition XVI
Ivan Kadar, Editor(s)

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