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How interaction methods affect image segmentation: user experience in the task

Hebbalaguppe, Ramya, McGuinness, Kevin orcid logoORCID: 0000-0003-1336-6477, Kuklyte, Jogile, Healy, Graham orcid logoORCID: 0000-0001-6429-6339, O'Connor, Noel E. orcid logoORCID: 0000-0002-4033-9135 and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2013) How interaction methods affect image segmentation: user experience in the task. In: The 1st IEEE Workshop on User-Centred Computer Vision (UCCV), 16-18 Jan 2013, Tampa, Florida, U.S.A..

Interactive image segmentation is extensively used in photo editing when the aim is to separate a foreground object from its background so that it is available for various applications. The goal of the interaction is to get an accurate segmentation of the object with the minimal amount of human effort. To improve the usability and user experience using interactive image segmentation we present three interaction methods and study the effect of each using both objective and subjective metrics, such as, accuracy, amount of effort needed, cognitive load and preference of interaction method as voted by users. The novelty of this paper is twofold. First , the evaluation of interaction methods is carried out with objective metrics such as object and boundary accuracies in tandem with subjective metrics to cross check if they support each other. Second, we analyze Electroencephalography (EEG) data obtained from subjects perform- ing the segmentation as an indicator of brain activity. The experimental results potentially give valuable cues for the development of easy-to-use yet efficient interaction methods for image segmentation.
Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Uncontrolled Keywords:image processing; image segmentation
Subjects:Computer Science > Interactive computer systems
Engineering > Signal processing
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > CLARITY: The Centre for Sensor Web Technologies
Published in: Proceedings of the 1st IEEE Workshop on User-Centred Computer Vision. . IEEE.
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland grant 07/CE/11147
ID Code:17835
Deposited On:26 Feb 2013 14:30 by Dr. Kevin McGuinness . Last Modified 24 Jan 2019 15:33

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