%0 Conference Proceedings %F BCITAG:EMBS2010 %A Pohlmeyer, Eric %A Jangraw, David %A Wang, Jun %A Chang, Shih-Fu %A Sajda, Paul %T Combining Computer and Human Vision into a BCI: Can the Whole Be Greater Than the Sum of Its Parts? %B The 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) %C Buenos Aires, Argentina %X Our group has been investigating the development of BCI systems for improving information delivery to a user, specifically systems for triaging image content based on what captures a user¡¯s attention. One of the systems we have developed uses single-trial EEG scores as noisy labels for a computer vision image retrieval system. In this paper we investigate how the noisy nature of the EEG-derived labels affects the resulting accuracy of the computer vision system. Specifically, we consider how the precision of the EEG scores affects the resulting precision of images retrieved by a graphbased transductive learning model designed to propagate image class labels based on image feature similarity and sparse labels %U http://www.ee.columbia.edu/ln/dvmm/publications/10/BCI_EMBS_2010.pdf %8 August %D 2010