Robust feature selection for large scale image retrieval
This paper addresses the problem of recognizing specific objects in very large datasets. A common approach has been based on the bag-of-words (BOW) method, in which local image features are clustered into visual words, providing memory savings through feature quantization. In this paper we take an...
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| Language: | English |
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University of British Columbia
2010
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| Online Access: | http://hdl.handle.net/2429/28474 |
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