dc.contributor.authorLiang, Hui
dc.contributor.authorYuan, Junsong
dc.contributor.authorThalmann, Daniel
dc.date.accessioned2013-08-02T03:23:09Z
dc.date.available2013-08-02T03:23:09Z
dc.date.copyright2012en_US
dc.date.issued2012
dc.identifier.citationLiang, H., Yuan, J., & Thalmann, D. (2012). Hand pose estimation by combining fingertip tracking and articulated ICP. Proceedings of the 11th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry - VRCAI '12, 87-90.en_US
dc.identifier.urihttp://hdl.handle.net/10220/12847
dc.description.abstractIn this paper we present a model-based framework for hand pose estimation, which relies on the depth and color image sequence input. The proposed framework adopts a divide-and-conquer scheme, and combines fingertip tracking and articulated iterative closest point approach to restore the hand motion. The tracked fingertip positions are used to provide an initial estimation of the hand pose, and articulated ICP are adopted for further refinement. Experiments on both synthetic data and real-world sequences show the hand pose estimation scheme can accurately capture the natural hand motion.en_US
dc.language.isoenen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering
dc.titleHand pose estimation by combining fingertip tracking and articulated ICPen_US
dc.typeConference Paper
dc.contributor.conferenceInternational Conference on Virtual-Reality Continuum and its Applications in Industry (11th : 2012 : Singapore)en_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.identifier.doihttp://dx.doi.org/10.1145/2407516.2407543


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