Rong, Y, Zheng, Y, Shao, T et al. (2 more authors) (2016) An Interactive Approach for Functional Prototype Recovery from a Single RGBD Image. Computational Visual Media, 2 (1). pp. 87-96. ISSN 2096-0433
Abstract
Inferring the functionality of an object from a single RGBD image is difficult for two reasons: lack of semantic information about the object, and missing data due to occlusion. In this paper, we present an interactive framework to recover a 3D functional prototype from a single RGBD image. Instead of precisely reconstructing the object geometry for the prototype, we mainly focus on recovering the object’s functionality along with its geometry. Our system allows users to scribble on the image to create initial rough proxies for the parts. After user annotation of high-level relations between parts, our system automatically jointly optimizes detailed joint parameters (axis and position) and part geometry parameters (size, orientation, and position). Such prototype recovery enables a better understanding of the underlying image geometry and allows for further physically plausible manipulation. We demonstrate our framework on various indoor objects with simple or hybrid functions.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2016. The articles published in this journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
Keywords: | functionality; cuboid proxy; prototype; part relations; shape analysis |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 15 Aug 2018 13:49 |
Last Modified: | 15 Aug 2018 13:49 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/s41095-016-0032-x |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:134217 |
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