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A key problem in biomedical imaging is the difficulty of combining human expertise with the power of advanced computing. Researchers at RIT are attacking this problem by utilizing visual perception techniques, computer modeling, and computational linguistics to infuse human expertise into content-based image retrieval systems.
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Our research is motivated by recognition that design of effective computing systems requires understanding of the relationships between people and technologies. A primary goal of human-centered computing is to strike the appropriate balance between human and machine capabilities and to integrate them in such a way that the system naturally supports the human end user. We focus on research towards intelligent human-computer interaction-using computers to enhance human performance involving complex cognitive activities, for example during visual reasoning and decision-making. Intelligent human-computer interaction combines human cognitive, physical, and affective factors to model human behavior for the design of adaptive systems.
There are several research threads in the HCC lab at RIT. These share a common experimental framework based on the idea that human behavior is both observable (e.g. motor, verbal, visual) and hidden (mental states) and that we can capture and model representative data via a variety of physical and physiological sensors. Our interdisciplinary group integrates methods and approaches of human-centered design, visual perception, imaging science, and computational linguistics to study the influence of perceptual expertise and domain knowledge on complex visual tasks. The HCCL closely collaborates with the Multidisciplinary Vision Research Lab (MVRL) in RIT’s Center for Imaging Science.