Sparse coding based VLAD for efficient image retrieval

Reddy, Mopuri K and Talur, Jayasimha and Babu, Venkatesh R (2014) Sparse coding based VLAD for efficient image retrieval. In: IEEE International Conference on Electronics, Computing and Communication Technologies (IEEE CONECCT), JAN 06-07, 2014, Indian Inst Sci, Bangalore, INDIA.

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Abstract

Representing images and videos in the form of compact codes has emerged as an important research interest in the vision community, in the context of web scale image/video search. Recently proposed Vector of Locally Aggregated Descriptors (VLAD), has been shown to outperform the existing retrieval techniques, while giving a desired compact representation. VLAD aggregates the local features of an image in the feature space. In this paper, we propose to represent the local features extracted from an image, as sparse codes over an over-complete dictionary, which is obtained by K-SVD based dictionary training algorithm. The proposed VLAD aggregates the residuals in the space of these sparse codes, to obtain a compact representation for the image. Experiments are performed over the `Holidays' database using SIFT features. The performance of the proposed method is compared with the original VLAD. The 4% increment in the mean average precision (mAP) indicates the better retrieval performance of the proposed sparse coding based VLAD.

Item Type:	Conference Proceedings
Series.:	IEEE International Conference on Electronics Computing and Communication Technologies
Publisher:	IEEE
Additional Information:	Copy right for this article belongs to the IEEE International Conference on Electronics, Computing and Communication Technologies (IEEE CONECCT), Indian Inst Sci, Bangalore, INDIA, JAN 06-07, 2014
Keywords:	Vector of Locally Aggregated Descriptors (VLAD); Image Retrieval; SIFT; Sparse Coding; mean average precision (mAP)
Department/Centre:	Division of Interdisciplinary Sciences > Supercomputer Education & Research Centre
Date Deposited:	01 Apr 2015 12:16
Last Modified:	01 Apr 2015 12:16
URI:	http://eprints.iisc.ac.in/id/eprint/51169

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