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Quality Control in Crowdsourced Object Segmentation

Cabezas, Ferran and Carlier, Axel and Salvador, Amaia and Giro I Nieto, Xavier and Charvillat, Vincent Quality Control in Crowdsourced Object Segmentation. (2015) In: IEEE International Conference on Image Processing (ICIP 2015), 27 September 2015 - 30 September 2015 (Québec, Canada).

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Abstract

This paper explores processing techniques to deal with noisy data in crowdsourced object segmentation tasks. We use the data collected with "Click'n'Cut", an online interactive segmentation tool, and we perform several experiments towards improving the segmentation results. First, we introduce different superpixel-based techniques to filter users' traces, and assess their impact on the segmentation result. Second, we present different criteria to detect and discard the traces from potential bad users, resulting in a remarkable increase in performance. Finally, we show a novel superpixel-based segmentation algorithm which does not require any prior filtering and is based on weighting each user's contribution according to his/her level of expertise.

Item Type:Conference or Workshop Item (Paper)
HAL Id:hal-01282046
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Universitat Politècnica de Catalunya - UPC (SPAIN)
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Deposited By: IRIT IRIT
Deposited On:10 Feb 2016 14:33

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