Paper
16 September 2003 3D ladar ATR based on recognition by parts
Erik Sobel, Joel Douglas, Gil Ettinger
Author Affiliations +
Abstract
LADAR imaging is unique in its potential to accurately measure the 3D surface geometry of targets. We exploit this 3D geometry to perform automatic target recognition on targets in the domain of military and civilian ground vehicles. Here we present a robust model based 3D LADAR ATR system which efficiently searches through target hypothesis space by reasoning hierarchically from vehicle parts up to identification of a whole vehicle with specific pose and articulation state. The LADAR data consists of one or more 3D point clouds generated by laser returns from ground vehicles viewed from multiple sensor locations. The key to this approach is an automated 3D registration process to precisely align and match multiple data views to model based predictions of observed LADAR data. We accomplish this registration using robust 3D surface alignment techniques which we have also used successfully in 3D medical image analysis applications. The registration routine seeks to minimize a robust 3D surface distance metric to recover the best six-degree-of-freedom pose and fit. We process the observed LADAR data by first extracting salient parts, matching these parts to model based predictions and hierarchically constructing and testing increasingly detailed hypotheses about the identity of the observed target. This cycle of prediction, extraction, and matching efficiently partitions the target hypothesis space based on the distinctive anatomy of the target models and achieves effective recognition by progressing logically from a target's constituent parts up to its complete pose and articulation state.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Erik Sobel, Joel Douglas, and Gil Ettinger "3D ladar ATR based on recognition by parts", Proc. SPIE 5094, Automatic Target Recognition XIII, (16 September 2003); https://doi.org/10.1117/12.486331
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Cited by 8 scholarly publications.
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KEYWORDS
3D modeling

3D acquisition

LIDAR

Automatic target recognition

Data modeling

Target recognition

3D image processing

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