Scale-Dependent/Invariant Local 3D Shape Descriptors for Fully Automatic Registration of Multiple Sets of Range Images

Abstract. Despite the ubiquitous use of range images in various computer vision applications, little has been investigated about the size variation of the local geometric structures captured in the range images. In this paper, we show that, through canonical geometric scale-space analysis, this geometric scale-variability embedded in a range image can be exploited as a rich source of discriminative information regarding the captured geometry. We extend previous work on geometric scale-space analysis of 3D models to analyze the scale-variability of a range image and to detect scale-dependent 3D features ? geometric features with their inherent scales. We derive novel local 3D shape descriptors that encode the local shape information within the inherent support region of each feature. We show that the resulting set of scale-dependent local shape descriptors can be used in an efficient hierarchical registration algorithm for aligning range images with the same global scale. We also show t...

• Type: Conference
• Year: 2008
• Where: ECCV
• Authors: John Novatnack, Ko Nishino
• Keywords: Canonical Geometric Scale-space, Computer Vision, ECCV 2008, Geometric Scale-space Analysis, Local 3D Shape, Local Geometric Structures, Local Shape Descriptors