Unsupervised Saliency Detection Based on 2D Gabor and Curvelets Transforms

Zhong, Sheng-hua, Liu, Yan, Shao, Ling and Wu, Gangshan (2011) Unsupervised Saliency Detection Based on 2D Gabor and Curvelets Transforms. In: ICIMCS '11 - The Third International Conference on Internet Multimedia Computing and Service, 5th - 7th August 2011, Chengdu, China.

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Abstract

Construction of saliency map in multimedia data is useful for applications in multimedia like object segmentation, quality assessment, and object recognition. In this paper, we propose a novel saliency map model called Gabor & Curvelets based Saliency Map (GCSMP) relying on 2D Gabor and Curvelet transforms. Compared with the traditional model based on DOG and wavelets, our model takes advantage of Gabor transform's spatial localization and Curvelet transform's edge and directional information. We also discuss the influence of center bias and object detectors in our model. Empirical validations on standard dataset demonstrate the effectiveness of the proposed technique.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Saliency map, 2D Gabor, Curvelet transform
Subjects:	G400 Computer Science
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Paul Burns
Date Deposited:	16 Jun 2015 14:58
Last Modified:	13 Oct 2019 00:31
URI:	http://nrl.northumbria.ac.uk/id/eprint/22969

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