A fast method for estimating the uncertainty in the location of image points in 3D recognition

Ilan Shimshoni

doi:10.1109/ICPR.1996.546094

A fast method for estimating the uncertainty in the location of image points in 3D recognition

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Efficient and robust model-based recognition systems need to be able to estimate reliably and quickly the possible locations of other model features in the image when a match of several model points to image points is given. Errors in the sensed data lead to uncertainty in the computed pose of the object which in turn lead to uncertainty in those positions. We present a very fast and accurate method for estimating these uncertainty regions. Our basic method deals with an initial match of three points and is extended using statistical methods to estimate the uncertainty region using initial matches of any size.

Original language	English
Title of host publication	Track A
Subtitle of host publication	Computer Vision
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	590-594
Number of pages	5
ISBN (Print)	081867282X, 9780818672828
DOIs	https://doi.org/10.1109/ICPR.1996.546094
State	Published - 1996
Externally published	Yes
Event	13th International Conference on Pattern Recognition, ICPR 1996 - Vienna, Austria Duration: 25 Aug 1996 → 29 Aug 1996

Publication series

Name	Proceedings - International Conference on Pattern Recognition
Volume	1
ISSN (Print)	1051-4651

Conference

Conference	13th International Conference on Pattern Recognition, ICPR 1996
Country/Territory	Austria
City	Vienna
Period	25/08/96 → 29/08/96

ASJC Scopus subject areas

Computer Vision and Pattern Recognition

Access to Document

10.1109/ICPR.1996.546094

Cite this

@inproceedings{58fbf83e0bbe4a7fb87ece73cec8ad95,

title = "A fast method for estimating the uncertainty in the location of image points in 3D recognition",

abstract = "Efficient and robust model-based recognition systems need to be able to estimate reliably and quickly the possible locations of other model features in the image when a match of several model points to image points is given. Errors in the sensed data lead to uncertainty in the computed pose of the object which in turn lead to uncertainty in those positions. We present a very fast and accurate method for estimating these uncertainty regions. Our basic method deals with an initial match of three points and is extended using statistical methods to estimate the uncertainty region using initial matches of any size.",

author = "Ilan Shimshoni",

year = "1996",

doi = "10.1109/ICPR.1996.546094",

language = "English",

isbn = "081867282X",

series = "Proceedings - International Conference on Pattern Recognition",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "590--594",

booktitle = "Track A",

address = "United States",

note = "13th International Conference on Pattern Recognition, ICPR 1996 ; Conference date: 25-08-1996 Through 29-08-1996",

}

Shimshoni, I 1996, A fast method for estimating the uncertainty in the location of image points in 3D recognition. in Track A: Computer Vision., 546094, Proceedings - International Conference on Pattern Recognition, vol. 1, Institute of Electrical and Electronics Engineers Inc., pp. 590-594, 13th International Conference on Pattern Recognition, ICPR 1996, Vienna, Austria, 25/08/96. https://doi.org/10.1109/ICPR.1996.546094

A fast method for estimating the uncertainty in the location of image points in 3D recognition. / Shimshoni, Ilan.
Track A: Computer Vision. Institute of Electrical and Electronics Engineers Inc., 1996. p. 590-594 546094 (Proceedings - International Conference on Pattern Recognition; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Shimshoni, Ilan

PY - 1996

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N2 - Efficient and robust model-based recognition systems need to be able to estimate reliably and quickly the possible locations of other model features in the image when a match of several model points to image points is given. Errors in the sensed data lead to uncertainty in the computed pose of the object which in turn lead to uncertainty in those positions. We present a very fast and accurate method for estimating these uncertainty regions. Our basic method deals with an initial match of three points and is extended using statistical methods to estimate the uncertainty region using initial matches of any size.

AB - Efficient and robust model-based recognition systems need to be able to estimate reliably and quickly the possible locations of other model features in the image when a match of several model points to image points is given. Errors in the sensed data lead to uncertainty in the computed pose of the object which in turn lead to uncertainty in those positions. We present a very fast and accurate method for estimating these uncertainty regions. Our basic method deals with an initial match of three points and is extended using statistical methods to estimate the uncertainty region using initial matches of any size.

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DO - 10.1109/ICPR.1996.546094

M3 - Conference contribution

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SN - 081867282X

SN - 9780818672828

T3 - Proceedings - International Conference on Pattern Recognition

SP - 590

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BT - Track A

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 13th International Conference on Pattern Recognition, ICPR 1996

Y2 - 25 August 1996 through 29 August 1996

ER -

A fast method for estimating the uncertainty in the location of image points in 3D recognition

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

On estimating the uncertainty in the location of image points in 3D recognition from match sets of different sizes

Cite this

A fast method for estimating the uncertainty in the location of image points in 3D recognition

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Related research output

On estimating the uncertainty in the location of image points in 3D recognition from match sets of different sizes

Cite this