Laga, Hamid and Jermyn, Ian H. and Kurtek, Sebastian and Srivastava, Anuj (2017) 'Elastic 3D shape analysis using square-root normal field representation.', in 2017 IEEE 56th Annual Conference on Decision and Control (CDC) : Melbourne, Australia, 12-15 December 2017 ; proceedings. Piscataway: IEEE, pp. 2711-2717.
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.
|Item Type:||Book chapter|
|Full text:||(AM) Accepted Manuscript|
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|Publisher Web site:||https://doi.org/10.1109/CDC.2017.8264053|
|Publisher statement:||© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.|
|Date accepted:||12 July 2017|
|Date deposited:||18 September 2017|
|Date of first online publication:||23 January 2018|
|Date first made open access:||No date available|
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