Please use this identifier to cite or link to this item: https://doi.org/10.1109/CVPR.2013.8
Title: 3D-based reasoning with blocks, support, and stability
Authors: Jia Z.
Gallagher A.
Saxena A.
Chen T. 
Issue Date: 2013
Citation: Jia Z., Gallagher A., Saxena A., Chen T. (2013). 3D-based reasoning with blocks, support, and stability. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition : 1-8. ScholarBank@NUS Repository. https://doi.org/10.1109/CVPR.2013.8
Abstract: 3D volumetric reasoning is important for truly understanding a scene. Humans are able to both segment each object in an image, and perceive a rich 3D interpretation of the scene, e.g., the space an object occupies, which objects support other objects, and which objects would, if moved, cause other objects to fall. We propose a new approach for parsing RGB-D images using 3D block units for volumetric reasoning. The algorithm fits image segments with 3D blocks, and iteratively evaluates the scene based on block interaction properties. We produce a 3D representation of the scene based on jointly optimizing over segmentations, block fitting, supporting relations, and object stability. Our algorithm incorporates the intuition that a good 3D representation of the scene is the one that fits the data well, and is a stable, self-supporting (i.e., one that does not topple) arrangement of objects. We experiment on several datasets including controlled and real indoor scenarios. Results show that our stability-reasoning framework improves RGB-D segmentation and scene volumetric representation.
Source Title: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
URI: http://scholarbank.nus.edu.sg/handle/10635/146097
ISSN: 10636919
DOI: 10.1109/CVPR.2013.8
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

72
checked on Oct 12, 2021

WEB OF SCIENCETM
Citations

59
checked on Oct 4, 2021

Page view(s)

47
checked on Oct 14, 2021

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.