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SALIENT OBJECT DETECTION VIA OBJECTNESS MEASURE

Srivatsa, Sai R and Babu, Venkatesh R (2015) SALIENT OBJECT DETECTION VIA OBJECTNESS MEASURE. In: IEEE International Conference on Image Processing (ICIP), SEP 27-30, 2015, Quebec City, CANADA, pp. 4481-4485.

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Official URL: http://arxiv.org/abs/1506.07363

Abstract

Salient object detection has become an important task in many image processing applications. The existing approaches exploit background prior and contrast prior to attain state of the art results. In this paper, instead of using background cues, we estimate the foreground regions in an image using objectness proposals and utilize it to obtain smooth and accurate saliency maps. We propose a novel saliency measure called `foreground connectivity' which determines how tightly a pixel or a region is connected to the estimated foreground. We use the values assigned by this measure as foreground weights and integrate these in an optimization framework to obtain the final saliency maps. We extensively evaluate the proposed approach on two benchmark databases and demonstrate that the results obtained are better than the existing state of the art approaches.

Item Type: Conference Proceedings
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Additional Information: Copy right for this article belongs to the IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Keywords: Image Saliency; Objectness Proposals; Image Segmentation; Superpixels
Department/Centre: Division of Information Sciences > Supercomputer Education & Research Centre
Date Deposited: 17 May 2016 05:43
Last Modified: 17 May 2016 05:43
URI: http://eprints.iisc.ernet.in/id/eprint/53847

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