Workshop on Hybrid Neuro-Computer Vision Systems

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Human visual systems represent the most complex information processing machines, with unique capabilities in recognizing objects at a glance, under varying poses, illuminations and scales. Recent advances in neuroimaging and sensing device makes this an exciting time in vision research. We can now see the brain "in action" while it performs complex visual recognition and scene understanding. Modalities such as EEG, MEG, fMRI, and eye tracking have yielded identifying neural correlates underlying information processing strategies used by the human visual processor. Recent efforts of computer vision research have also yielded some promising successes, though mostly for constrained problems. This workshop brings together world-leaders in the fields of visual neuroscience, neural computing, and computer vision to discuss our current understanding of how the brain is able to rapidly recognize objects and analyze a visual scene relative to the capabilities of state-of-the-art computer vision systems. Emphasis is placed on identifying synergies between human and machine vision and potential neural interfaces that could be used to create hybrid vision systems. An additional focus is on rapid scene analysis and recognition, rather than reasoning and higher level cognition. The workshop aims at broader impacts in facilitating fruitful interaction among experts from three separate fields. The major outcome includes a report that documents in detail the grand research challenges, opportunities, and concrete recommendations of actions for NSF and other funding agencies.