A statistical analysis of 3D structure tensor features generated from LADAR imagery
Miguel Ordaz, Estille Whittenberger, Donald E. Waagen, Donald R. Hulsey · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
Extraction and efficient representation of informative structure from data is the goal of pattern recognition. Efficient and effective parametric and nonparametric representations for capturing the geometry of three-dimensional objects are an area of current research. Tang and Medioni have proposed tensor representations for characterization and reconstruction of surfaces. 3-D structure tensors are extracted by mapping surface geometries using a rank-2 covariant tensor. Distributional differences between representations of objects of interest can (theoretically) be used for target matching and identification. This paper analyzes the statistical distributions of tensor representation extracted from 3-D LADAR imagery and quantifies a measure of divergence between images of three vehicles as a function of tensor feature support size.