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Author, Editor(s)

Author(s):

Sunkel, Martin
Jansen, Silke
Wand, Michael
Seidel, Hans-Peter

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BibTeX cite key*:

Sunkel2013

Title

Title*:

A Correlated Parts Model for Object Detection in Large 3D Scans

Journal

Journal Title*:

Computer Graphics Forum (Proc. EUROGRAPHICS)

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Language:

English

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Vol, No, pp, Date

Volume*:

32

Number:

2

Publishing Date:

May 2013

Pages*:

1-8

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(LaTeX) Abstract:

This paper addresses the problem of detecting objects in 3D scans according to object classes learned from sparse user annotation.
We model objects belonging to a class by a set of fully correlated parts, encoding dependencies between local shapes of different parts as well as their relative spatial arrangement.
For an efficient and comprehensive retrieval of instances belonging to a class of interest, we introduce a new approximate inference scheme and a corresponding planning procedure. We extend our technique to hierarchical composite structures, reducing training effort and modeling spatial relations between detected instances.
We evaluate our method on a number of real-world 3D scans and demonstrate its benefits as well as the performance of the new inference algorithm.

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Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Computer Graphics Group

Audience:

experts only

Appearance:

MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort


BibTeX Entry:

@ARTICLE{Sunkel2013,
AUTHOR = {Sunkel, Martin and Jansen, Silke and Wand, Michael and Seidel, Hans-Peter},
TITLE = {A Correlated Parts Model for Object Detection in Large 3D Scans},
JOURNAL = {Computer Graphics Forum (Proc. EUROGRAPHICS)},
YEAR = {2013},
NUMBER = {2},
VOLUME = {32},
PAGES = {1--8},
MONTH = {May},
}


Entry last modified by Silke Jansen, 01/30/2014
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Editor(s)
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Created
01/31/2013 01:59:14 PM
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Editor
Silke Jansen



Edit Date
01/31/2013 01:59:14 PM