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Proceedings Paper

3D orientation vector estimation for subcomponents of space object imagery
Author(s): Xun Du; Stanley C. Ahalt; Bruce E. Stribling
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Paper Abstract

We describe a model-based image analysis system which automatically estimates the 3D orientation vector of satellites and their sub-components by analyzing images obtained from a ground-based optical surveillance system. We adopt a two-step approach: pose estimates are derived from comparisons with a model database; pose refinements are derived from photogrammetric information. The model database is formed by representing each available training image by a set of derived geometric primitives. To obtain fast access to the model database and to increase the probability of early successful matching, a novel index hashing method is introduced. We present recent results which include our efforts at isolating and estimating orientation vectors from degraded imagery on a significant database of satellites. We also discuss the problems our system encounters with some of the images, and the solutions we are implementing to significantly improve the system.

Paper Details

Date Published: 28 July 1997
PDF: 11 pages
Proc. SPIE 3068, Signal Processing, Sensor Fusion, and Target Recognition VI, (28 July 1997); doi: 10.1117/12.280820
Show Author Affiliations
Xun Du, The Ohio State Univ. (United States)
Stanley C. Ahalt, The Ohio State Univ. (United States)
Bruce E. Stribling, Air Force Maui Optical Station (United States)

Published in SPIE Proceedings Vol. 3068:
Signal Processing, Sensor Fusion, and Target Recognition VI
Ivan Kadar, Editor(s)

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