Shen, Chao-Hui, Fu, Hongbo, Chen, Kang and Hu, Shi-Min ![]() |
Preview |
PDF
- Published Version
Download (19MB) | Preview |
Abstract
This paper presents a technique that allows quick conversion of acquired low-quality data from consumer-level scanning devices to high-quality 3D models with labeled semantic parts and meanwhile their assembly reasonably close to the underlying geometry. This is achieved by a novel structure recovery approach that is essentially local to global and bottom up, enabling the creation of new structures by assembling existing labeled parts with respect to the acquired data. We demonstrate that using only a small-scale shape repository, our part assembly approach is able to faithfully recover a variety of high-level structures from only a single-view scan of man-made objects acquired by the Kinect system, containing a highly noisy, incomplete 3D point cloud and a corresponding RGB image.
Item Type: | Article |
---|---|
Date Type: | Publication |
Status: | Published |
Schools: | Computer Science & Informatics |
Subjects: | Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) |
Publisher: | ACM |
ISSN: | 0730-0301 |
Date of First Compliant Deposit: | 30 March 2016 |
Last Modified: | 03 May 2023 01:54 |
URI: | https://orca.cardiff.ac.uk/id/eprint/45706 |
Citation Data
Cited 118 times in Scopus. View in Scopus. Powered By Scopus® Data
Actions (repository staff only)
![]() |
Edit Item |