Conference paper
Elastic 3D shape analysis using Square-Root normal field representation
IEEE 56th Annual Conference on Decision and Control (CDC) 2017 (Melbourne, VIC, 12/12/2017–15/12/2017)
2017
Abstract
Shape is an important physical property of natural and man-made 3D objects that characterizes their external appearances. Understanding differences between shapes, and modeling the variability within and across shape classes, hereinafter referred to as shape analysis, are problems fundamental to many applications, ranging from computer vision and computer graphics to biology and medicine. This paper provides an overview of some of the recent techniques for studying the shape of 3D objects that undergo non-rigid deformations including bending and stretching. We will mainly focus on a new representation called the square-root normal field (SRNF), discuss its properties, and show its application in the analysis of the shape of various types of objects, including human body shapes, anatomical organs such as carpal bones, and hand-drawn 2D sketches. We will show how the representation is used for (1) jointly computing correspondences and geodesics; (2) computing summary statistics such as means and modes of variations; and (3) exploring shape variability in a collection of 3D objects.
Details
- Title
- Elastic 3D shape analysis using Square-Root normal field representation
- Authors/Creators
- H. Laga (Author/Creator) - Murdoch UniversityI.H. Jermyn (Author/Creator) - Durham UniversityS. Kurtek (Author/Creator) - The Ohio State UniversityA. Srivastava (Author/Creator) - Florida State University
- Conference
- IEEE 56th Annual Conference on Decision and Control (CDC) 2017 (Melbourne, VIC, 12/12/2017–15/12/2017)
- Identifiers
- 991005542618207891
- Murdoch Affiliation
- School of Engineering and Information Technology
- Language
- English
- Resource Type
- Conference paper
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