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dc.contributor.authorLee, Jinhan
dc.contributor.authorKiser, Jeffrey F.
dc.contributor.authorBobick, Aaron F.
dc.contributor.authorThomaz, Andrea L.
dc.date.accessioned2011-03-23T12:48:22Z
dc.date.available2011-03-23T12:48:22Z
dc.date.issued2011
dc.identifier.citationJ. Lee, J.F. Kiser, A.F. Bobick and A.L.Thomaz, "Vision-based Contingency Detection" In Proceedings of the International Conference on Human-Robot Interaction (HRI), 2011.en_US
dc.identifier.urihttp://hdl.handle.net/1853/38254
dc.description© ACM, 2011. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version will be published in Proceedings of the 6th International Conference on Human-Robot Interaction (HRI), 2011. http://doi.acm.orgen_US
dc.description.abstractWe present a novel method for the visual detection of a contingent response by a human to the stimulus of a robot action. Contingency is de ned as a change in an agent's be- havior within a speci c time window in direct response to a signal from another agent; detection of such responses is essential to assess the willingness and interest of a human in interacting with the robot. Using motion-based features to describe the possible contingent action, our approach as- sesses the visual self-similarity of video subsequences cap- tured before the robot exhibits its signaling behavior and statistically models the typical graph-partitioning cost of separating an arbitrary subsequence of frames from the oth- ers. After the behavioral signal, the video is similarly ana- lyzed and the cost of separating the after-signal frames from the before-signal sequences is computed; a lower than typ- ical cost indicates likely contingent reaction. We present a preliminary study in which data were captured and analyzed for algorithmic performance.en_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectContingency detectionen_US
dc.subjectHuman-robot interactionen_US
dc.subjectResponse detectionen_US
dc.titleVision-based Contingency Detectionen_US
dc.typePre-printen_US
dc.typeProceedings
dc.contributor.corporatenameGeorgia Institute of Technology. School of Interactive Computing
dc.publisher.originalAssociation for Computing Machinery


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