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LABEL CONSISTENT MATRIX FACTORIZATION BASED HASHING FOR CROSS-MODAL RETRIEVAL

Mandal, Devraj and Biswas, Soma (2017) LABEL CONSISTENT MATRIX FACTORIZATION BASED HASHING FOR CROSS-MODAL RETRIEVAL. In: 24th IEEE International Conference on Image Processing (ICIP), SEP 17-20, 2017, Beijing, PEOPLES R CHINA, pp. 2901-2905.

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Official URL: http://dx.doi.org/10.1109/ICIP.2017.8296813

Abstract

Matrix factorization-based hashing has been very effective in addressing the cross-modal retrieval task. In this work, we propose a novel supervised hashing approach utilizing the concepts of matrix factorization which can seamlessly incorporate the label information. In the proposed approach, the latent factors for each individual modality are generated and then converted to the more discriminative label space using modality specific linear transformations. In the first stage of the approach, the hash codes are learnt using an alternating minimization algorithm and in the next stage, modality specific hash functions are learned to convert the original features of the cross-modal data into the hash code domain. In addition, we also propose an extension of the approach for handling very large amounts of data during the training stage. Extensive experiments performed on the single label Wiki, and the multi-labeled MirFlickr and NUS-WIDE datasets show the effectiveness of the proposed approach.

Item Type: Conference Proceedings
Additional Information: Copy right for this article belong to IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Depositing User: Id for Latest eprints
Date Deposited: 07 May 2018 19:00
Last Modified: 07 May 2018 19:00
URI: http://eprints.iisc.ac.in/id/eprint/59789

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