Statistical Shape Analysis of Multi-Object Complexes

An important goal of statistical shape analysis is the discrimination between populations of objects, exploring group differences in morphology not explained by standard volumetric analysis. Certain applications additionally require analysis of objects in their embedding context by joint statistical analysis of sets of interrelated objects. In this paper, we present a framework for discriminant analysis of populations of 3-D multi-object sets. In view of the driving medical applications, a skeletal object parametrization of shape is chosen since it naturally encodes thickening, bending and twisting. In a multi-object setting, we not only consider a joint analysis of sets of shapes but also must take into account differences in pose. Statistics on features of medial descriptions and pose parameters, which include rotational frames and distances, uses a Riemannian symmetric space instead of the standard Euclidean metric. Our choice of discriminant method is the distance weighted discrim...

• Type: Conference
• Year: 2007
• Where: CVPR
• Authors: Kevin Gorczowski, Martin Styner, Ja-Yeon Jeong, J. S. Marron, Joseph Piven, Heather Cody Hazlett, Stephen M. Pizer, Guido Gerig
• Keywords: 3-d Multi-object Sets, Computer Vision, CVPR 2007, Discriminant Analysis, Joint Statistical Analysis, Multi-object Analysis, Statistical Shape Analysis