Elementary block extraction for mobile ...
Document type :
Communication dans un congrès avec actes
Title :
Elementary block extraction for mobile image search
Author(s) :
Mennesson, José [Auteur]
FOX MIIRE [LIFL]
Tirilly, Pierre [Auteur]
FOX MIIRE [LIFL]
Martinet, Jean [Auteur]
FOX MIIRE [LIFL]
FOX MIIRE [LIFL]
Tirilly, Pierre [Auteur]
FOX MIIRE [LIFL]
Martinet, Jean [Auteur]
FOX MIIRE [LIFL]
Scientific editor(s) :
IEEE
Conference title :
International Conference on Image Processing
City :
Paris
Country :
France
Start date of the conference :
2014-10-27
Publication date :
2014-10
English keyword(s) :
mobile computing
feature selection
feature extraction
visual words repetitiveness
natural scenes
mobile image search
elementary blocks
elementary block extraction
content-based image retrieval method
SIFT descriptors
Index Terms-image retrieval
bag-of-words
visual fea-ture selection
building images
mobile applications
feature selection
feature extraction
visual words repetitiveness
natural scenes
mobile image search
elementary blocks
elementary block extraction
content-based image retrieval method
SIFT descriptors
Index Terms-image retrieval
bag-of-words
visual fea-ture selection
building images
mobile applications
HAL domain(s) :
Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
Informatique [cs]/Recherche d'information [cs.IR]
Informatique [cs]/Recherche d'information [cs.IR]
English abstract : [en]
In this paper, we propose an original content-based image retrieval method using bag-of-words dedicated to building matching on mobile devices. In the literature, the repetitiveness of visual words in natural scenes, and ...
Show more >In this paper, we propose an original content-based image retrieval method using bag-of-words dedicated to building matching on mobile devices. In the literature, the repetitiveness of visual words in natural scenes, and especially in building images, has been demonstrated. Assuming images are composed of a set of elementary blocks, we represent them using only a few well-chosen features. In the context of image search on mobile devices, this allows to considerably reduce the size of the data to be sent to the server. This method has been experimented using SIFT descriptors on three well-known databases. Experimental results show that this method can outperform the standard bag-of-words approach while reducing the number of features used to represent images. Moreover, this general framework can be used in conjunction with any kind of descriptors and indexing methods.Show less >
Show more >In this paper, we propose an original content-based image retrieval method using bag-of-words dedicated to building matching on mobile devices. In the literature, the repetitiveness of visual words in natural scenes, and especially in building images, has been demonstrated. Assuming images are composed of a set of elementary blocks, we represent them using only a few well-chosen features. In the context of image search on mobile devices, this allows to considerably reduce the size of the data to be sent to the server. This method has been experimented using SIFT descriptors on three well-known databases. Experimental results show that this method can outperform the standard bag-of-words approach while reducing the number of features used to represent images. Moreover, this general framework can be used in conjunction with any kind of descriptors and indexing methods.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
European Project :
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