Parsing IKEA Objects: Fine Pose Estimation
Name
Torralba_Parsing IKEA.pdf
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1.52 MB
Format
Adobe PDF
Checksum (MD5)
050e849026810fc31e786acb162a7858
Author(s)
Pirsiavash, Hamed
Torralba, Antonio
Lim, Joseph Jaewhan
Date Issued
December 2013
Journal
Proceedings of the 2013 IEEE International Conference on Computer Vision
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Lim, Joseph J., Hamed Pirsiavash, and Antonio Torralba. “Parsing IKEA Objects: Fine Pose Estimation.” 2013 IEEE International Conference on Computer Vision (December 2013).
Version
Author's final manuscript
Abstract
We address the problem of localizing and estimating the fine-pose of objects in the image with exact 3D models. Our main focus is to unify contributions from the 1970s with recent advances in object detection: use local keypoint detectors to find candidate poses and score global alignment of each candidate pose to the image. Moreover, we also provide a new dataset containing fine-aligned objects with their exactly matched 3D models, and a set of models for widely used objects. We also evaluate our algorithm both on object detection and fine pose estimation, and show that our method outperforms state-of-the art algorithms.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/ICCV.2013.372
