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Improving object segmentation by using EEG signals and rapid serial visual presentation

Mohedano, Eva, Healy, Graham orcid logoORCID: 0000-0001-6429-6339, McGuinness, Kevin orcid logoORCID: 0000-0003-1336-6477, Giró-i-Nieto, Xavier orcid logoORCID: 0000-0002-9935-5332, O'Connor, Noel E. orcid logoORCID: 0000-0002-4033-9135 and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2015) Improving object segmentation by using EEG signals and rapid serial visual presentation. Multimedia Tools and Applications, 74 (22). pp. 10137-10159. ISSN 1573-7721

Abstract
This paper extends our previous work on the potential of EEG-based brain computer interfaces to segment salient objects in images. The proposed system analyzes the Event Related Potentials (ERP) generated by the rapid serial visual presentation of windows on the image. The detection of the P300 signal allows estimating a saliency map of the image, which is used to seed a semi-supervised object segmentation algorithm. Thanks to the new contributions presented in this work, the average Jaccard index was improved from $0.47$ to $0.66$ when processed in our publicly available dataset of images, object masks and captured EEG signals. This work also studies alternative architectures to the original one, the impact of object occupation in each image window, and a more robust evaluation based on statistical analysis and a weighted F-score.
Metadata
Item Type:Article (Published)
Refereed:No
Subjects:Computer Science > Machine learning
Engineering > Signal processing
Computer Science > Image processing
DCU Faculties and Centres:Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Publisher:Springer (Kluwer)
Official URL:http://dx.doi.org/10.1007/s11042-015-2805-0
Copyright Information:© 2015 Springer. The original publication is available at www.springerlink.com
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland
ID Code:20691
Deposited On:29 Oct 2015 15:31 by Eva Mohedano Robles . Last Modified 05 Jan 2022 14:14
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