Model based pose estimation of articulated and constrained objects

Yaacov Hel-Or; Michael Werman

doi:10.1007/3-540-57956-7_31

Model based pose estimation of articulated and constrained objects

Yaacov Hel-Or, Michael Werman

The Rachel and Selim Benin School of Engineering and Computer Science

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

3 Scopus citations

Abstract

This paper presents a method for localization of modeled objects that is general enough to cover articulated and other types of constrained models. The flexibility between components of the model are expressed as spatial constraints which are fused into the pose estimation process. The constraint fusion assists in obtaining a precise and stable pose of each object's component and in finding the correct interpretation. The proposed method can handle any constraint (including inequalities) between any number of different components of the model. The framework is based on Kalman filtering.

Original language	English
Title of host publication	Computer Vision — ECCV 1994 - 3rd European Conference on Computer Vision, Proceedings
Editors	Jan-Olof Eklundh
Publisher	Springer Verlag
Pages	262-273
Number of pages	12
ISBN (Print)	9783540579564
DOIs	https://doi.org/10.1007/3-540-57956-7_31
State	Published - 1994
Event	3rd European Conference on Computer Vision, ECCV 1994 - Stockholm, Sweden Duration: 2 May 1994 → 6 May 1994

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	800 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd European Conference on Computer Vision, ECCV 1994
Country/Territory	Sweden
City	Stockholm
Period	2/05/94 → 6/05/94

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 1994.

Access to Document

10.1007/3-540-57956-7_31

Cite this

Hel-Or, Y., & Werman, M. (1994). Model based pose estimation of articulated and constrained objects. In J.-O. Eklundh (Ed.), Computer Vision — ECCV 1994 - 3rd European Conference on Computer Vision, Proceedings (pp. 262-273). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 800 LNCS). Springer Verlag. https://doi.org/10.1007/3-540-57956-7_31

Hel-Or, Yaacov ; Werman, Michael. / Model based pose estimation of articulated and constrained objects. Computer Vision — ECCV 1994 - 3rd European Conference on Computer Vision, Proceedings. editor / Jan-Olof Eklundh. Springer Verlag, 1994. pp. 262-273 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{adfa0ce7371448ffaa8e641f599ac3df,

title = "Model based pose estimation of articulated and constrained objects",

abstract = "This paper presents a method for localization of modeled objects that is general enough to cover articulated and other types of constrained models. The flexibility between components of the model are expressed as spatial constraints which are fused into the pose estimation process. The constraint fusion assists in obtaining a precise and stable pose of each object's component and in finding the correct interpretation. The proposed method can handle any constraint (including inequalities) between any number of different components of the model. The framework is based on Kalman filtering.",

author = "Yaacov Hel-Or and Michael Werman",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 1994.; 3rd European Conference on Computer Vision, ECCV 1994 ; Conference date: 02-05-1994 Through 06-05-1994",

year = "1994",

doi = "10.1007/3-540-57956-7_31",

language = "אנגלית",

isbn = "9783540579564",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "262--273",

editor = "Jan-Olof Eklundh",

booktitle = "Computer Vision — ECCV 1994 - 3rd European Conference on Computer Vision, Proceedings",

address = "גרמניה",

}

Hel-Or, Y & Werman, M 1994, Model based pose estimation of articulated and constrained objects. in J-O Eklundh (ed.), Computer Vision — ECCV 1994 - 3rd European Conference on Computer Vision, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 800 LNCS, Springer Verlag, pp. 262-273, 3rd European Conference on Computer Vision, ECCV 1994, Stockholm, Sweden, 2/05/94. https://doi.org/10.1007/3-540-57956-7_31

Model based pose estimation of articulated and constrained objects. / Hel-Or, Yaacov; Werman, Michael.
Computer Vision — ECCV 1994 - 3rd European Conference on Computer Vision, Proceedings. ed. / Jan-Olof Eklundh. Springer Verlag, 1994. p. 262-273 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 800 LNCS).

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

TY - GEN

T1 - Model based pose estimation of articulated and constrained objects

AU - Hel-Or, Yaacov

AU - Werman, Michael

PY - 1994

Y1 - 1994

N2 - This paper presents a method for localization of modeled objects that is general enough to cover articulated and other types of constrained models. The flexibility between components of the model are expressed as spatial constraints which are fused into the pose estimation process. The constraint fusion assists in obtaining a precise and stable pose of each object's component and in finding the correct interpretation. The proposed method can handle any constraint (including inequalities) between any number of different components of the model. The framework is based on Kalman filtering.

AB - This paper presents a method for localization of modeled objects that is general enough to cover articulated and other types of constrained models. The flexibility between components of the model are expressed as spatial constraints which are fused into the pose estimation process. The constraint fusion assists in obtaining a precise and stable pose of each object's component and in finding the correct interpretation. The proposed method can handle any constraint (including inequalities) between any number of different components of the model. The framework is based on Kalman filtering.

UR - http://www.scopus.com/inward/record.url?scp=85027615465&partnerID=8YFLogxK

U2 - 10.1007/3-540-57956-7_31

DO - 10.1007/3-540-57956-7_31

M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???

AN - SCOPUS:85027615465

SN - 9783540579564

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 262

EP - 273

BT - Computer Vision — ECCV 1994 - 3rd European Conference on Computer Vision, Proceedings

A2 - Eklundh, Jan-Olof

PB - Springer Verlag

T2 - 3rd European Conference on Computer Vision, ECCV 1994

Y2 - 2 May 1994 through 6 May 1994

ER -

Hel-Or Y, Werman M. Model based pose estimation of articulated and constrained objects. In Eklundh JO, editor, Computer Vision — ECCV 1994 - 3rd European Conference on Computer Vision, Proceedings. Springer Verlag. 1994. p. 262-273. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-57956-7_31

Model based pose estimation of articulated and constrained objects

Abstract

Publication series

Conference

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this