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Proceedings Paper

The effects of different shape-based metrics on the identification of military targets from 3D ladar data
Author(s): Gregory J. Meyer; James R. Weber
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Paper Abstract

The choice of shape metrics is important to effectively identify three-dimensional targets. The performance (expressed as a probability of correct classification) of four metrics using point clouds of military targets rendered using Irma, a government tool that simulates the output of an active ladar system, is compared across multiple ranges, sampling densities, target types, and noise levels. After understanding the range of operating conditions a classifier would be expected to see in the field, a process for determining the upper-bound of a classifier and the significance of this result is assessed. Finally, the effect of sampling density and variance in the position estimates on classification performance is shown. Classification performance significantly decreases when sampling density exceeds 10 degrees and the voxelized histogram metric outperforms the other three metrics used in this paper because of its performance in high-noise environments. Most importantly, this paper highlights a step-by-step method to test and evaluate shape metrics using accurate target models.

Paper Details

Date Published: 26 January 2006
PDF: 11 pages
Proc. SPIE 6056, Three-Dimensional Image Capture and Applications VII, 60560H (26 January 2006); doi: 10.1117/12.641253
Show Author Affiliations
Gregory J. Meyer, Air Force Research Lab. (United States)
James R. Weber, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 6056:
Three-Dimensional Image Capture and Applications VII
Brian D. Corner; Peng Li; Matthew Tocheri, Editor(s)

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