FPM: Fine Pose Parts-Based Model with 3D CAD Models
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Torralba_FPM Fine.pdf
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1.93 MB
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Author(s)
Khosla, Aditya
Torralba, Antonio
Lim, Joseph Jaewhan
Date Issued
2014
Journal
Computer Vision – ECCV 2014
Publisher
Springer-Verlag
Citation
Lim, Joseph J., Aditya Khosla, and Antonio Torralba. “FPM: Fine Pose Parts-Based Model with 3D CAD Models.” Lecture Notes in Computer Science (2014): 478–493.
Version
Author's final manuscript
Abstract
We introduce a novel approach to the problem of localizing objects in an image and estimating their fine-pose. Given exact CAD models, and a few real training images with aligned models, we propose to leverage the geometric information from CAD models and appearance information from real images to learn a model that can accurately estimate fine pose in real images. Specifically, we propose FPM, a fine pose parts-based model, that combines geometric information in the form of shared 3D parts in deformable part based models, and appearance information in the form of objectness to achieve both fast and accurate fine pose estimation. Our method significantly outperforms current state-of-the-art algorithms in both accuracy and speed.
MIT Department
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/10.1007/978-3-319-10599-4_31
