Defining the ideal criteria for stable skeletonisation in object point clouds

Wen, Qingmeng ORCID: https://orcid.org/0000-0002-8972-4042, Tafrishi, Seyed Amir ORCID: https://orcid.org/0000-0001-9829-3144, Ji, Ze ORCID: https://orcid.org/0000-0002-8968-9902 and Lai, Yu-Kun ORCID: https://orcid.org/0000-0002-2094-5680 2024. Defining the ideal criteria for stable skeletonisation in object point clouds. Presented at: 40th Anniversary of the IEEE Conference on Robotics and Automation (ICRA@40), Rotterdam, Netherlands, 23-26 September 2024.

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Abstract

In recent years, there has been notable interest in skeletonization methods for 3D object models, driven by their broad applicability in fields such as computer graphics and robotics. However, existing studies have lacked a clear quantitative standard for evaluating skeletonization quality. This paper extends prior research on point cloud skeletonization to examine the intrinsic properties of the process across diverse object shapes, aiming to provide intuitive insights into the quality of resulting skeletons. Additionally, we propose a novel concept of stable convergence of contraction, leveraging distributions of geometric curvature and vectorial normal changes.

Item Type:	Conference or Workshop Item (Speech)
Date Type:	Completion
Status:	Unpublished
Schools:	Engineering
Date of First Compliant Deposit:	14 October 2024
Date of Acceptance:	30 June 2024
Last Modified:	07 Nov 2024 17:15
URI:	https://orca.cardiff.ac.uk/id/eprint/172110

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