Abstract 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.

Url http://doras.dcu.ie/20562/1/icmr193s.pdf

Collections Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> Subject = Engineering: Signal processing
Ireland -> Dublin City University -> Subject = Computer Science: Computer engineering
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: INSIGHT Centre for Data Analytics
Ireland -> Dublin City University -> Subject = Engineering
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres
Ireland -> Dublin City University -> Publication Type = Conference or Workshop Item
Ireland -> Dublin City University -> Subject = Computer Science: Interactive computer systems
Ireland -> Dublin City University -> Subject = Computer Science
Ireland -> Dublin City University -> Subject = Computer Science: Information retrieval
Ireland -> Dublin City University -> Subject = Computer Science: Machine learning