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.
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Funders:
Science Foundation Ireland (SFI), grant number SFI/12/RC/2289, Spanish Ministerio de Econom ́ıa y Competitividad and the European Regional Development Fund (ERDF), GeoForce GTX Titan Z from NVIDIA Corporation
ID Code:
20562
Deposited On:
21 Jul 2015 10:49 by
Eva Mohedano Robles
. Last Modified 06 Nov 2019 14:25