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The 3rd Canadian Conference on Computer and Robot Vision (CRV'06)
Generic Detection of Multi-Part Objects by High-Level Analysis
Quebec City, Quebec, Canada
June 07-June 09
ISBN: 0-7695-2542-3
ASCII Text
x 
 
Jean-Francois Bernier, Robert Bergevin, "Generic Detection of Multi-Part Objects by High-Level Analysis," Computer and Robot Vision, Canadian Conference, pp. 2, The 3rd Canadian Conference on Computer and Robot Vision (CRV'06), 2006.
 
 
BibTex
x
 
@article{ 10.1109/CRV.2006.36,
author = {Jean-Francois Bernier and Robert Bergevin},
title = {Generic Detection of Multi-Part Objects by High-Level Analysis},
journal ={Computer and Robot Vision, Canadian Conference},
volume = {0},
year = {2006},
isbn = {0-7695-2542-3},
pages = {2},
doi = {http://doi.ieeecomputersociety.org/10.1109/CRV.2006.36},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Computer and Robot Vision, Canadian Conference
TI - Generic Detection of Multi-Part Objects by High-Level Analysis
SN - 0-7695-2542-3
SP
EP
A1 - Jean-Francois Bernier,
A1 - Robert Bergevin,
PY - 2006
KW - null
VL - 0
JA - Computer and Robot Vision, Canadian Conference
ER -
 
Jean-Francois Bernier, Laval University, Quebec, Canada
Robert Bergevin, Laval University, Quebec, Canada
A method is proposed to detect multi-part man-made or natural objects in complex images. It consists in first extracting simple curves and straight lines from the edge map. Then, a search tree is expanded by selecting and ordering the segmented primitives on the basis of generic local and global grouping criteria. The set of partial contours provided by the parallel search are combined into more complex forms. Global scores produce a sorted list of potential object silhouettes.
Citation:
Jean-Francois Bernier, Robert Bergevin, "Generic Detection of Multi-Part Objects by High-Level Analysis," crv, pp.2, The 3rd Canadian Conference on Computer and Robot Vision (CRV'06), 2006
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