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Exploring EEG for object detection and retrieval
Mohedano, Eva; Salvador, Amaia; Porta Caubet, Sergi; Giró-i-Nieto, Xavier; McGuinness, Kevin; Healy, Graham; O'Connor, Noel E.; Smeaton, Alan F.
This paper explores the potential for using Brain Computer Interfaces (BCI) as a relevance feedback mechanism in contentbased image retrieval. Several experiments are performed using a rapid serial visual presentation (RSVP) of images at different rates (5Hz and 10Hz) on 8 users with different degrees of familiarization with BCI and the dataset. We compare the feedback from the BCI and mouse-based interfaces in a subset of TRECVid images, finding that, when users have limited time to annotate the images, both interfaces are comparable in performance. Comparing our best users in a retrieval task, we found that EEG-based relevance feedback can outperform mouse-based feedback.
Keyword(s): Interactive computer systems; Machine learning; Signal processing; Computer engineering; Information retrieval
Publication Date:
2015
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: Dublin City University
Citation(s): Mohedano, Eva, Salvador, Amaia, Porta Caubet, Sergi, Giró-i-Nieto, Xavier ORCID: 0000-0002-9935-5332 <https://orcid.org/0000-0002-9935-5332>, McGuinness, Kevin ORCID: 0000-0003-1336-6477 <https://orcid.org/0000-0003-1336-6477>, Healy, Graham ORCID: 0000-0001-6429-6339 <https://orcid.org/0000-0001-6429-6339>, O'Connor, Noel E. ORCID: 0000-0002-4033-9135 <https://orcid.org/0000-0002-4033-9135> and Smeaton, Alan F. ORCID: 0000-0003-1028-8389 <https://orcid.org/0000-0003-1028-8389> (2015) Exploring EEG for object detection and retrieval. In: 2015 ACM International Conference on Multimedia Retrieval (ICMR 2015), 23-26 Jun 2015, Shanghai, China. ISBN 978-1-4503-3274-3
Publisher(s): Association for Computing Machinery
File Format(s): application/pdf
Related Link(s): http://doras.dcu.ie/20562/1/icmr193s.pdf
First Indexed: 2015-07-23 05:05:20 Last Updated: 2019-02-09 06:21:40