Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Neurophysiologically driven image triage: a pilot study
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Enhancing target detection using a hybrid human-computer system
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Quantifying target spotting performances with complex geoscientific imagery using ERP P300 responses
International Journal of Human-Computer Studies
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The problem of extracting information from large collections of imagery is a challenge with few good solutions. Computers typically cannot interpret imagery as effectively as humans can, and manual analysis tools are slow. The research reported here explores the feasibility of speeding up manual image analysis by tapping into split second perceptual judgments using electroencephalograph sensors. Experimental results show that a combination of neurophysiological signals and overt physical responses--detected while a user views imagery in high speed bursts of approximately 10 images per second--provide a basis for detecting targets within large image sets. Results show an approximately six-fold, statistically significant, reduction in the time required to detect targets at high accuracy levels compared to conventional broad-area image analysis.