Reference TypeConference Proceedings
Citation KeyPimentelFoAraúCrucGoue:2013:EfEfSk
Author1 Pimentel Filho, Carlos Alberto Fraga
2 Araújo, Arnaldo de Albuquerque
3 Crucianu, Michel
4 Gouet-Brunet, Valérie
Affiliation1 Federal University of Minas Gerais
2 Federal University of Minas Gerais
3 Conservatoire National des Arts et Métiers - CEDRIC
4 IGN - Laboratoire MATIS
TitleSketch-Finder: efficient and effective sketch-based retrieval for large image collections
Conference NameConference on Graphics, Patterns and Images, 26 (SIBGRAPI)
EditorBoyer, Kim
Hirata, Nina
Nedel, Luciana
Silva, Claudio
Book TitleProceedings
DateAug. 5-8, 2013
Publisher CityLos Alamitos
PublisherIEEE Computer Society
Conference LocationArequipa, Peru
Keywordssketch-based image retrieval, multimedia indexing, scalability.
AbstractAmong various image retrieval approaches, the use of sketches lets one express a precise visual query with simple and widespread means. The challenge consists in finding a content representation that allows you to effectively compare sketches and images, while supporting efficient retrieval in order to make the system scalable. We put forward a sketch-based image retrieval solution where sketches and natural image contours are represented and compared in the wavelet domain. The relevant information regarding query sketches and image content has, thus, a compact representation that can be readily employed by an efficient index for retrieval by similarity. Furthermore, with this solution, the balance between effectiveness and efficiency can be easily modified in order to adapt to the available resources. A comparative evaluation with a state-of-the-art method on the Paris dataset and a subset with 535K images of the ImageNet dataset shows that our solution can preserve effectiveness while being more than one order of magnitude faster.
Tertiary TypeFull Paper
Size5974 KiB
Number of Files1
Target FilePID2854709.pdf
Last Update2013:
Metadata Last Update2020: administrator {D 2013}
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History2013-07-11 19:18:09 :: -> administrator ::
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Access Date2020, Nov. 25