Title :
Relevance feedback in Surfimage
Author :
Meilhac, Christophe ; Mitschke, Matthias ; Nastar, Chahab
Author_Institution :
Inst. Nat. de Recherche en Inf. et Autom., Le Chesnay, France
Abstract :
Relevance feedback is one of the strong components of Surfimage, the INRIA content-based image retrieval system. Relevance feedback is about learning from user interaction, and is useful in tasks like query refinement and multiple queries. We present two relevance feedback techniques currently implemented in Surfimage
Keywords :
content-based retrieval; relevance feedback; INRIA; Surfimage; content-based image retrieval; multiple queries; query refinement; relevance feedback; Cities and towns; Engines; Feedback; Image databases; Image retrieval; Information retrieval; Layout; Nearest neighbor searches; Robustness; Spatial databases;
Conference_Titel :
Applications of Computer Vision, 1998. WACV '98. Proceedings., Fourth IEEE Workshop on
Conference_Location :
Princeton, NJ
Print_ISBN :
0-8186-8606-5
DOI :
10.1109/ACV.1998.732899
