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» Optimizing Multi-Feature Queries for Image Databases
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ICASSP
2010
IEEE
13 years 7 months ago
Searching with expectations
Handling large amounts of data, such as large image databases, requires the use of approximate nearest neighbor search techniques. Recently, Hamming embedding methods such as spec...
Harsimrat Sandhawalia, Herve Jegou
SIGIR
2008
ACM
13 years 7 months ago
Learning to reduce the semantic gap in web image retrieval and annotation
We study in this paper the problem of bridging the semantic gap between low-level image features and high-level semantic concepts, which is the key hindrance in content-based imag...
Changhu Wang, Lei Zhang 0001, Hong-Jiang Zhang
PAMI
2008
208views more  PAMI 2008»
13 years 7 months ago
BoostMap: An Embedding Method for Efficient Nearest Neighbor Retrieval
This paper describes BoostMap, a method for efficient nearest neighbor retrieval under computationally expensive distance measures. Database and query objects are embedded into a v...
Vassilis Athitsos, Jonathan Alon, Stan Sclaroff, G...
SIGIR
1999
ACM
13 years 11 months ago
Content-Based Retrieval Using Heuristic Search
The fast growth of multimedia information in image and video databases has triggered research on efficient retrieval methods. This paper deals with structural queries, a type of c...
Dimitris Papadias, Marios Mantzourogiannis, Panos ...
ICDE
2000
IEEE
120views Database» more  ICDE 2000»
14 years 8 months ago
Deflating the Dimensionality Curse Using Multiple Fractal Dimensions
Nearest neighbor queries are important in many settings, including spatial databases (Find the k closest cities) and multimedia databases (Find the k most similar images). Previou...
Bernd-Uwe Pagel, Flip Korn, Christos Faloutsos