dc.contributor.author | Lee, Jinhan | |
dc.contributor.author | Kiser, Jeffrey F. | |
dc.contributor.author | Bobick, Aaron F. | |
dc.contributor.author | Thomaz, Andrea L. | |
dc.date.accessioned | 2011-03-23T12:48:22Z | |
dc.date.available | 2011-03-23T12:48:22Z | |
dc.date.issued | 2011 | |
dc.identifier.citation | J. 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.uri | http://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.org | en_US |
dc.description.abstract | We 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.iso | en_US | en_US |
dc.publisher | Georgia Institute of Technology | en_US |
dc.subject | Contingency detection | en_US |
dc.subject | Human-robot interaction | en_US |
dc.subject | Response detection | en_US |
dc.title | Vision-based Contingency Detection | en_US |
dc.type | Pre-print | en_US |
dc.type | Proceedings | |
dc.contributor.corporatename | Georgia Institute of Technology. School of Interactive Computing | |
dc.publisher.original | Association for Computing Machinery | |