article

3-D to 2-D Pose Determination with Regions

Authors:

Ronen BasriAuthors Info & Claims

International Journal of Computer Vision, Volume 34, Issue 2-3

Pages 123 - 145

https://doi.org/10.1023/A:1008135819955

Published: 01 October 1999 Publication History

Abstract

This paper presents a novel approach to parts-based object recognition in the presence of occlusion. We focus on the problem of determining the pose of a 3-D object from a single 2-D image when convex parts of the object have been matched to corresponding regions in the image. We consider three types of occlusions: self-occlusion, occlusions whose locus is identified in the image, and completely arbitrary occlusions. We show that in the first two cases this is a convex optimization problem, derive efficient algorithms, and characterize their performance. For the last case, we prove that the problem of finding valid poses is computationally hard, but provide an efficient, approximate algorithm. This work generalizes our previous work on region-based object recognition, which focused on the case of planar models.

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Cited By

Mcinroy JQi Z(2008)A Novel Pose Estimation Algorithm Based on Points to Regions CorrespondenceJournal of Mathematical Imaging and Vision10.1007/s10851-007-0045-230:2(195-207)Online publication date: 1-Feb-2008
https://dl.acm.org/doi/10.1007/s10851-007-0045-2
Lerner RRivlin ERotstein H(2006)Pose and Motion Recovery from Feature Correspondences and a Digital Terrain MapIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2006.19228:9(1404-1417)Online publication date: 1-Sep-2006
https://dl.acm.org/doi/10.1109/TPAMI.2006.192
Bhat KSeitz SPopovic J(2002)Computing the Physical Parameters of Rigid-Body Motion from VideoProceedings of the 7th European Conference on Computer Vision-Part I10.5555/645315.649162(551-565)Online publication date: 28-May-2002
https://dl.acm.org/doi/10.5555/645315.649162
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3-D to 2-D Pose Determination with Regions

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Published In

cover image International Journal of Computer Vision

International Journal of Computer Vision Volume 34, Issue 2-3

Special issue on computer vision research at NEC Research Institute

Nov. 1999

127 pages

ISSN:0920-5691

Editors:
Takeo Kanade
Carnegie Mellon Univ., Pittsburgh, PA
,
Olivier Faugeras
INRIA, France
,
Ingemar Cox
NEC Research Institute, Princeton, NJ

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Copyright © Copyright © 1999 Kluwer Academic Publishers.

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Kluwer Academic Publishers

United States

Publication History

Published: 01 October 1999

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Cited By

Mcinroy JQi Z(2008)A Novel Pose Estimation Algorithm Based on Points to Regions CorrespondenceJournal of Mathematical Imaging and Vision10.1007/s10851-007-0045-230:2(195-207)Online publication date: 1-Feb-2008
https://dl.acm.org/doi/10.1007/s10851-007-0045-2
Lerner RRivlin ERotstein H(2006)Pose and Motion Recovery from Feature Correspondences and a Digital Terrain MapIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2006.19228:9(1404-1417)Online publication date: 1-Sep-2006
https://dl.acm.org/doi/10.1109/TPAMI.2006.192
Bhat KSeitz SPopovic J(2002)Computing the Physical Parameters of Rigid-Body Motion from VideoProceedings of the 7th European Conference on Computer Vision-Part I10.5555/645315.649162(551-565)Online publication date: 28-May-2002
https://dl.acm.org/doi/10.5555/645315.649162
Basri RJacobs D(2001)Projective Alignment with RegionsIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/34.92270923:5(519-527)Online publication date: 1-May-2001
https://dl.acm.org/doi/10.1109/34.922709
Rosenfeld A(2000)Classifying the Literature Related to Computer Vision and Image AnalysisComputer Vision and Image Understanding10.1006/cviu.2000.085179:2(308-323)Online publication date: 1-Aug-2000
https://dl.acm.org/doi/10.1006/cviu.2000.0851

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