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Interactive segmentation: a scalable superpixel-based method

Mathieu, Bérengère and Crouzil, Alain and Puel, Jean-Baptiste Interactive segmentation: a scalable superpixel-based method. (2017) Journal of Electronic Imaging, 26 (6). 1-18. ISSN 1017-9909

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Official URL: https://doi.org/10.1117/1.JEI.26.6.061606


This paper addresses the problem of interactive multiclass segmentation of images. We propose a fast and efficient new interactive segmentation method called superpixel alpha fusion (SaF). From a few strokes drawn by a user over an image, this method extracts relevant semantic objects. To get a fast calculation and an accurate segmentation, SaF uses superpixel oversegmentation and support vector machine classification. We compare SaF with competing algorithms by evaluating its performances on reference benchmarks. We also suggest four new datasets to evaluate the scalability of interactive segmentation methods, using images from some thousand to several million pixels. We conclude with two applications of SaF.

Item Type:Article
Additional Information:https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging/volume-26/issue-6/061606/Interactive-segmentation-a-scalable-superpixel-based-method/10.1117/1.JEI.26.6.061606.short
HAL Id:hal-03512910
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Ecole Nationale Supérieure de Formation de l'Enseignement Agricole - ENSFEA (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Laboratory name:
Deposited On:07 Nov 2018 10:10

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