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Proceedings Paper

Contextual object understanding through geospatial analysis and reasoning (COUGAR)
Author(s): Joel Douglas; Matthew Antone; James Coggins; Bradley J. Rhodes; Erik Sobel; Frank Stolle; Lori Vinciguerra; Majid Zandipour; Yu Zhong
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Paper Abstract

Military operations in urban areas often require detailed knowledge of the location and identity of commonly occurring objects and spatial features. The ability to rapidly acquire and reason over urban scenes is critically important to such tasks as mission and route planning, visibility prediction, communications simulation, target recognition, and inference of higher-level form and function. Under DARPA's Urban Reasoning and Geospatial ExploitatioN Technology (URGENT) Program, the BAE Systems team has developed a system that combines a suite of complementary feature extraction and matching algorithms with higher-level inference and contextual reasoning to detect, segment, and classify urban entities of interest in a fully automated fashion. Our system operates solely on colored 3D point clouds, and considers object categories with a wide range of specificity (fire hydrants, windows, parking lots), scale (street lights, roads, buildings, forests), and shape (compact shapes, extended regions, terrain). As no single method can recognize the diverse set of categories under consideration, we have integrated multiple state-of-the-art technologies that couple hierarchical associative reasoning with robust computer vision and machine learning techniques. Our solution leverages contextual cues and evidence propagation from features to objects to scenes in order to exploit the combined descriptive power of 3D shape, appearance, and learned inter-object spatial relationships. The result is a set of tools designed to significantly enhance the productivity of analysts in exploiting emerging 3D data sources.

Paper Details

Date Published: 4 May 2009
PDF: 11 pages
Proc. SPIE 7335, Automatic Target Recognition XIX, 733506 (4 May 2009); doi: 10.1117/12.823438
Show Author Affiliations
Joel Douglas, BAE Systems (United States)
Matthew Antone, BAE Systems (United States)
James Coggins, BAE Systems (United States)
Bradley J. Rhodes, BAE Systems (United States)
Erik Sobel, BAE Systems (United States)
Frank Stolle, BAE Systems (United States)
Lori Vinciguerra, BAE Systems (United States)
Majid Zandipour, BAE Systems (United States)
Yu Zhong, BAE Systems (United States)


Published in SPIE Proceedings Vol. 7335:
Automatic Target Recognition XIX
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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