Dominant orientation templates for real-time detection of texture-less objects

Stefan Hinterstoisser; Vincent Lepetit; Slobodan Ilic; Pascal Fua; Nassir Navab

doi:10.1109/CVPR.2010.5539908

Dominant orientation templates for real-time detection of texture-less objects

Stefan Hinterstoisser, Vincent Lepetit, Slobodan Ilic, Pascal Fua, Nassir Navab

Informatics 16 - Chair of Computer Aided Medical Procedures

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

205 Scopus citations

Abstract

We present a method for real-time 3D object detection that does not require a time consuming training stage, and can handle untextured objects. At its core, is a novel template representation that is designed to be robust to small image transformations. This robustness based on dominant gradient orientations lets us test only a small subset of all possible pixel locations when parsing the image, and to represent a 3D object with a limited set of templates. We show that together with a binary representation that makes evaluation very fast and a branch-and-bound approach to efficiently scan the image, it can detect untextured objects in complex situations and provide their 3D pose in real-time.

Original language	English
Title of host publication	2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010
Pages	2257-2264
Number of pages	8
DOIs	https://doi.org/10.1109/CVPR.2010.5539908
State	Published - 2010
Event	2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010 - San Francisco, CA, United States Duration: 13 Jun 2010 → 18 Jun 2010

Publication series

Name	Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)	1063-6919

Conference

Conference	2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010
Country/Territory	United States
City	San Francisco, CA
Period	13/06/10 → 18/06/10

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10.1109/CVPR.2010.5539908

Cite this

Hinterstoisser, S., Lepetit, V., Ilic, S., Fua, P., & Navab, N. (2010). Dominant orientation templates for real-time detection of texture-less objects. In 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010 (pp. 2257-2264). Article 5539908 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). https://doi.org/10.1109/CVPR.2010.5539908

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title = "Dominant orientation templates for real-time detection of texture-less objects",

abstract = "We present a method for real-time 3D object detection that does not require a time consuming training stage, and can handle untextured objects. At its core, is a novel template representation that is designed to be robust to small image transformations. This robustness based on dominant gradient orientations lets us test only a small subset of all possible pixel locations when parsing the image, and to represent a 3D object with a limited set of templates. We show that together with a binary representation that makes evaluation very fast and a branch-and-bound approach to efficiently scan the image, it can detect untextured objects in complex situations and provide their 3D pose in real-time.",

author = "Stefan Hinterstoisser and Vincent Lepetit and Slobodan Ilic and Pascal Fua and Nassir Navab",

year = "2010",

doi = "10.1109/CVPR.2010.5539908",

language = "English",

isbn = "9781424469840",

series = "Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition",

pages = "2257--2264",

booktitle = "2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010",

note = "2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010 ; Conference date: 13-06-2010 Through 18-06-2010",

}

Hinterstoisser, S, Lepetit, V, Ilic, S, Fua, P & Navab, N 2010, Dominant orientation templates for real-time detection of texture-less objects. in 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010., 5539908, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 2257-2264, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010, San Francisco, CA, United States, 13/06/10. https://doi.org/10.1109/CVPR.2010.5539908

Dominant orientation templates for real-time detection of texture-less objects. / Hinterstoisser, Stefan; Lepetit, Vincent; Ilic, Slobodan et al.
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010. 2010. p. 2257-2264 5539908 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).

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

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AB - We present a method for real-time 3D object detection that does not require a time consuming training stage, and can handle untextured objects. At its core, is a novel template representation that is designed to be robust to small image transformations. This robustness based on dominant gradient orientations lets us test only a small subset of all possible pixel locations when parsing the image, and to represent a 3D object with a limited set of templates. We show that together with a binary representation that makes evaluation very fast and a branch-and-bound approach to efficiently scan the image, it can detect untextured objects in complex situations and provide their 3D pose in real-time.

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M3 - Conference contribution

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Hinterstoisser S, Lepetit V, Ilic S, Fua P, Navab N. Dominant orientation templates for real-time detection of texture-less objects. In 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010. 2010. p. 2257-2264. 5539908. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). doi: 10.1109/CVPR.2010.5539908

Dominant orientation templates for real-time detection of texture-less objects

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