Kaliciak, Leszek; Wang, Lei; Song, Dawei; Zhang, Peng and Hou, Yuexian
(2011).
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| URL: | http://cs.tju.edu.cn/faculty/dsong/papers/fulltext... |
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Abstract
Multimedia information retrieval suffers from the semantic gap, a difference between human perception and machine representation of images. In order to reduce the gap, a quantum theory inspired theoretical framework for integration of text and visual features has been proposed. This article is a followup work on this model. Previously, two relatively straight forward statistical approaches for making associations between dimensions of both feature spaces were employed, but with unsatisfactory results. In this paper, we propose to alleviate the problem regarding unannotated images by projecting them onto subspaces representing visual context and by incorporating a quantum-like measurement. The proposed principled approach extends the traditional vector space model (VSM) and seamlessly integrates with the tensor-based framework. Here,we experimentally test the novel association methods in a small-scale experiment.
| Item Type: | Conference Item |
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| Copyright Holders: | 2011 Springer-Verlag |
| ISSN: | 0302-9743 |
| Extra Information: | Quantum Interaction
5th International Symposium, QI 2011, Aberdeen, UK, June 26-29, 2011, Revised Selected Papers Editors:Dawei Song, Massimo Melucci, Ingo Frommholz, Peng Zhang, Lei Wang, Sachi Arafat Lecture Notes in Computer Science, Volume 7052 2011 ISBN: 978-3-642-24970-9 (Print) ISBN: 978-3-642-24971-6 (Online) pp.217-222 |
| Keywords: | multimedia retrieval; quantum theory; image annotation; tensor product |
| Academic Unit/Department: | Mathematics, Computing and Technology Mathematics, Computing and Technology > Computing |
| Related URLs: | |
| Item ID: | 34940 |
| Depositing User: | Mary Mcmahon |
| Date Deposited: | 26 Oct 2012 09:17 |
| Last Modified: | 26 Oct 2012 21:06 |
| URI: | http://oro.open.ac.uk/id/eprint/34940 |
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