A Novel Web Image Re-Ranking Approach Based On Query Specific Semantic Signatures
Author(s):
Pooja P. Dutta , NSIT; Anand Chauhan, NSITKeywords:
Web Image, Web Image Re – Ranking, Image Query, Content Based Retrieval, Semantic Signatures, Visual Similarities, Keywords ExpansionAbstract:
Image re-ranking, is an effective way to improve the results of web-based image search. Given a query keyword, a pool of images are initailly retrieved primarily based on textual data, the remaining images are re-ranked based on their visual similarities with the query image corresponding to the user input. A major challenge is that the similarities of visual features don't well correlate with images’ semantic meanings that interpret users’ search intention. Recently people proposed to match pictures in a semantic space that used attributes or reference categories closely associated with the semantic meanings of images as basis. Even though, learning a universal visual semantic space to characterize extremely diverse images from the internet is troublesome and inefficient. In this thesis, we propose a completely distinctive image re-ranking framework that learns completely different semantic spaces for numerous query keywords automatically at the on-line stage. The visual features of images are projected into their corresponding semantic spaces to induce semantic signatures. At the online stage, images are re-ranked by scrutiny their semantic signatures obtained from the semantic spaces such that by the query keyword. The proposed query-specific semantic signatures considerably improve both the accuracy and efficiency of image re-ranking.
Other Details:
| Manuscript Id | : | J4RV2I3047 |
| Published in | : | Volume : 2, Issue : 3 |
| Publication Date | : | 01/06/2016 |
| Page(s) | : | 88-93 |
