Target acquisition in three-dimensional data

David W. Webster; Eran Marcus; David M. Doria

doi:10.1117/12.487408

16 September 2003 Target acquisition in three-dimensional data

David W. Webster, Eran Marcus, David M. Doria

Proceedings Volume 5094, Automatic Target Recognition XIII; (2003) https://doi.org/10.1117/12.487408
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

We describe a method of acquiring ground vehicles in cluttered environments by making use of three dimensional geometrical features. Our approach exploits a wide spectrum of shape and structure attributes to achieve very high performance target detection and scene interpretation capabilities. The system we present begins with extraction of terrain from an observed scene, and proceeds to cluster the remaining points into macroscopic objects. These objects are then subjected to a series of tests that use textural and structural measures at multiple scales to discriminate targets from natural and manmade clutter. We present experimental results on a new set of synthetic three-dimensional data, demonstrating excellent target detection and false alarm suppression performance.

Citation Download Citation

David W. Webster, Eran Marcus, and David M. Doria "Target acquisition in three-dimensional data", Proc. SPIE 5094, Automatic Target Recognition XIII, (16 September 2003); https://doi.org/10.1117/12.487408

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