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CIVR
2008
Springer

FISH: a practical system for fast interactive image search in huge databases

9 years 4 months ago
FISH: a practical system for fast interactive image search in huge databases
The problem of search and retrieval of images using relevance feedback has attracted tremendous attention in recent years from the research community. A real-world-deployable interactive image retrieval system must (1) be accurate, (2) require minimal user-interaction, (3) be efficient, (4) be scalable to large collections (millions) of images, and (5) support multi-user sessions. For good accuracy, we need effective methods for learning the relevance of image features based on user feedback, both within a user-session and across sessions. Efficiency and scalability require a good index structure for retrieving results. The index structure must allow for the relevance of image features to continually change with fresh queries and user-feedback. The state-of-the-art methods available today each address only a subset of these issues. In this paper, we build a complete system FISH
Pradhee Tandon, Piyush Nigam, Vikram Pudi, C. V. J
Added 18 Oct 2010
Updated 18 Oct 2010
Type Conference
Year 2008
Where CIVR
Authors Pradhee Tandon, Piyush Nigam, Vikram Pudi, C. V. Jawahar
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