Exploring EEG for object detection and retrieval
Document typeConference lecture
PublisherAssociation for Computing Machinery (ACM)
Rights accessOpen Access
This paper explores the potential for using Brain Computer Interfaces (BCI) as a relevance feedback mechanism in content-based 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.
CitationMohedano, E., Salvador, A., Porta, S., Giro, X., Healy, G., McGuinness, K., O'Connor, N., Smeaton, A. Exploring EEG for object detection and retrieval. A: ACM International Conference on Multimedia Retrieval. "ICMR '15 Proceedings of the 5th ACM on International Conference on Multimedia Retrieval". Shanghai: Association for Computing Machinery (ACM), 2015, p. 591-594.