Xu, K;
Kim, VG;
Huang, Q;
Mitra, N;
Kalogerakis, E;
(2016)
Data-driven shape analysis and processing.
In: Mitra, NJ, (ed.)
SA '16: SIGGRAPH ASIA 2016 Course.
Association for Computing Machinery (ACM): New York, NY, USA.
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Abstract
Data-driven methods serve an increasingly important role in discovering geometric, structural, and semantic relationships between shapes. In contrast to traditional approaches that process shapes in isolation of each other, data-driven methods aggregate information from 3D model collections to improve the analysis, modeling and editing of shapes. Through reviewing the literature, we provide an overview of the main concepts and components of these methods, as well as discuss their application to classification, segmentation, matching, reconstruction, modeling and exploration, as well as scene analysis and synthesis. We conclude our report with ideas that can inspire future research in data-driven shape analysis and processing.
| Type: | Proceedings paper |
|---|---|
| Title: | Data-driven shape analysis and processing |
| Event: | SIGGRAPH ASIA 2016 Course (SA '16) |
| ISBN-13: | 9781450345385 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/2988458.2988473 |
| Publisher version: | http://dx.doi.org/10.1145/2988458.2988473 |
| Language: | English |
| Additional information: | Copyright © The Authors 2016. |
| Keywords: | machine learning, geometry processing, geometry analysis |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/1536531 |
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