Presentation 2008-12-19
Multiclass VisualRank : Image Ranking Method in Clustered Subsets Based on Visual Features
Mitsuru AMBAI, Yuichi YOSHIDA,
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Abstract(in English) In this paper, we propose Multiclass VisualRank, a method that expands the idea of VisualRank into more than one category of images. VisualRank uses visual features to refine ranking scores of images retrieved from image search engine; however, the results tend to be occupied by similar images. It is preferable that the top results include relevant yet diverse images. Multiclass VisualRank divides images retrieved from search engines into several categories based on distinctive patterns of visual features, and gives ranking within the category. This method displays the images in multiple sequences. Each of the sequence represents the image category and is sorted by their ranking scores. In this way, representative images that have distinct objects yet relate to the same search words are obtained. A clustering algorithm is applied to weighted graph derived from the visual similarities to extract clusters composed of similar images. Experimental results show that the proposed method can produce diverse results without losing precision.
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Keyword(in English) VisualRank / Image Retrieval / Clustering / Ranking
Paper # PRMU2008-178
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Conference Information
Committee PRMU
Conference Date 2008/12/11(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Multiclass VisualRank : Image Ranking Method in Clustered Subsets Based on Visual Features
Sub Title (in English)
Keyword(1) VisualRank
Keyword(2) Image Retrieval
Keyword(3) Clustering
Keyword(4) Ranking
1st Author's Name Mitsuru AMBAI
1st Author's Affiliation Denso IT Laboratory, Inc.()
2nd Author's Name Yuichi YOSHIDA
2nd Author's Affiliation Denso IT Laboratory, Inc.
Date 2008-12-19
Paper # PRMU2008-178
Volume (vol) vol.108
Number (no) 363
Page pp.pp.-
#Pages 6
Date of Issue