Eric Pohlmeyer, David Jangraw, Jun Wang, Shih-Fu Chang, Paul Sajda. Combining Computer and Human Vision into a BCI: Can the Whole Be Greater Than the Sum of Its Parts?. In The 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Buenos Aires, Argentina, August 2010.
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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
@InProceedings{BCITAG:EMBS2010,
Author = {Pohlmeyer, Eric and Jangraw, David and Wang, Jun and Chang, Shih-Fu and Sajda, Paul},
Title = {Combining Computer and Human Vision into a BCI: Can the Whole Be Greater Than the Sum of Its Parts?},
BookTitle = {The 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
Address = {Buenos Aires, Argentina},
Month = {August},
Year = {2010}
}
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