Web Image Re-Ranking Using Query-Specific Semantic Signatures

a novel image re-ranking framework, which automatically offline learns different visual semantic spaces for different query keywords through keyword expansions. The visual features of images are projected into their related visual semantic spaces to get semantic signatures. At the online stage, images are re-ranked
by comparing their semantic signatures obtained from the
visual semantic space specified by the query keyword. The
new approach significantly improves both the accuracy and
efficiency of image re-ranking. The original visual features
of thousands of dimensions can be projected to the semantic
signatures as short as 25 dimensions. Experimental results
show that 20% 􀀀 35% relative improvement has been
achieved on re-ranking precisions compared with the stateof-
the-art methods.

Тэги:

#Image_Re-ranking #seamntic_signatures #Query-specific

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