Localizing 3D cuboids in single-view images
Name
4842-localizing-3d-cuboids-in-single-view-images.pdf
Description
Published version
Size
5.46 MB
Format
Adobe PDF
Checksum (MD5)
84ef0f8837883cf25b8cc2a8913a3e7f
Author(s)
Xiao, Jianxiong
Russell, Bryan
Torralba, Antonio
Date Issued
2012
Journal
Advances in Neural Information Processing Systems
Publisher
Neural Information Processing Systems Foundation
Citation
Xiao, Jianxiong et al. "Localizing 3D cuboids in single-view images." Advances in Neural Information Processing Systems (NIPS 2012), 25, 2012. © 2012 NIPS Foundation
Version
Final published version
Abstract
In this paper we seek to detect rectangular cuboids and localize their corners in uncalibrated single-view images depicting everyday scenes. In contrast to recent approaches that rely on detecting vanishing points of the scene and grouping line segments to form cuboids, we build a discriminative parts-based detector that models the appearance of the cuboid corners and internal edges while enforcing consistency to a 3D cuboid model. Our model copes with different 3D viewpoints and aspect ratios and is able to detect cuboids across many different object categories. We introduce a database of images with cuboid annotations that spans a variety of indoor and outdoor scenes and show qualitative and quantitative results on our collected database. Our model out-performs baseline detectors that use 2D constraints alone on the task of localizing cuboid corners.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://papers.nips.cc/paper/4842-localizing-3d-cuboids-in-single-view-images
