DocumentCode
3475653
Title
Sill image object categorization using 2D models
Author
Petre, R.-D. ; Zaharia, T.
Author_Institution
ARTEMIS Dept., TELECOM SudParis, Evry, France
fYear
2011
fDate
6-8 Sept. 2011
Firstpage
347
Lastpage
351
Abstract
This paper proposes a novel recognition scheme for semantic labeling of 2D objects present in still images. The principle consists of matching unknown 2D objects with categorized 3D models in order to associate the semantics of the 3D object to the image. We tested our new recognition framework by using the MPEG-7 and Princeton 3D model databases in order to label unknown images randomly selected from the web. Experiments show that such a system can achieve recognition rate up to 70.4%.
Keywords
image classification; image matching; video coding; visual databases; 2D models; MPEG-7; Princeton 3D model databases; categorized 3D models; image matching; image recognition; semantic labeling; still image object categorization; Indexing; Object recognition; Shape; Solid modeling; Three dimensional displays; Transform coding; 2D and 3D shape descriptors; 2D/3D indexing; indexing and retrieval; object classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Consumer Electronics - Berlin (ICCE-Berlin), 2011 IEEE International Conference on
Conference_Location
Berlin
Print_ISBN
978-1-4577-0233-4
Type
conf
DOI
10.1109/ICCE-Berlin.2011.6031874
Filename
6031874
Link To Document