Facet Matching from an Uncalibrated Pair of Images
Summary :
Since for recognition tasks it is known that planar invariants are more easily obtained than others, decomposing a scene in terms of planar parts becomes very interresting. This paper presents a new approach to find the projections of planar surfaces in a pair of images. For this task we introduce the facet concept defined by linked edges (chains) and corners. We use collineations as projective information to match and verify their planarity. Our contribution consists in obtaining from an uncalibrated stereo pair of images a match of "planar" chains based on matched corners. Collineations are constrained by the fundamental matrix information and a Kalman filter approach is used to refine its computation.
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- IEICE TRANSACTIONS on Information Vol.E83-D No.7 pp.1395-1399
- Publication Date
- 2000/07/25
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- Special Section PAPER (Special Issue on Machine Vision Applications)
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Lukas THEILER, Houda CHABBI, "Facet Matching from an Uncalibrated Pair of Images" in IEICE TRANSACTIONS on Information,
vol. E83-D, no. 7, pp. 1395-1399, July 2000, doi: .
Abstract: Since for recognition tasks it is known that planar invariants are more easily obtained than others, decomposing a scene in terms of planar parts becomes very interresting. This paper presents a new approach to find the projections of planar surfaces in a pair of images. For this task we introduce the facet concept defined by linked edges (chains) and corners. We use collineations as projective information to match and verify their planarity. Our contribution consists in obtaining from an uncalibrated stereo pair of images a match of "planar" chains based on matched corners. Collineations are constrained by the fundamental matrix information and a Kalman filter approach is used to refine its computation.
URL: https://global.ieice.org/en_transactions/information/10.1587/e83-d_7_1395/_p
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@ARTICLE{e83-d_7_1395,
author={Lukas THEILER, Houda CHABBI, },
journal={IEICE TRANSACTIONS on Information},
title={Facet Matching from an Uncalibrated Pair of Images},
year={2000},
volume={E83-D},
number={7},
pages={1395-1399},
abstract={Since for recognition tasks it is known that planar invariants are more easily obtained than others, decomposing a scene in terms of planar parts becomes very interresting. This paper presents a new approach to find the projections of planar surfaces in a pair of images. For this task we introduce the facet concept defined by linked edges (chains) and corners. We use collineations as projective information to match and verify their planarity. Our contribution consists in obtaining from an uncalibrated stereo pair of images a match of "planar" chains based on matched corners. Collineations are constrained by the fundamental matrix information and a Kalman filter approach is used to refine its computation.},
keywords={},
doi={},
ISSN={},
month={July},}
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TY - JOUR
TI - Facet Matching from an Uncalibrated Pair of Images
T2 - IEICE TRANSACTIONS on Information
SP - 1395
EP - 1399
AU - Lukas THEILER
AU - Houda CHABBI
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E83-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2000
AB - Since for recognition tasks it is known that planar invariants are more easily obtained than others, decomposing a scene in terms of planar parts becomes very interresting. This paper presents a new approach to find the projections of planar surfaces in a pair of images. For this task we introduce the facet concept defined by linked edges (chains) and corners. We use collineations as projective information to match and verify their planarity. Our contribution consists in obtaining from an uncalibrated stereo pair of images a match of "planar" chains based on matched corners. Collineations are constrained by the fundamental matrix information and a Kalman filter approach is used to refine its computation.
ER -
English
