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FullHand: Markerless Skeleton-based Tracking for Free-Hand Interaction

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons79499

Sridhar,  Srinath
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45610

Theobalt,  Christian
Computer Graphics, MPI for Informatics, Max Planck Society;

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Volltexte (frei zugänglich)

MPI-I-2016-4-002.pdf
(Verlagsversion), 15MB

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Zitation

Sridhar, S., Bailly, G., Heydrich, E., Oulasvirta, A., & Theobalt, C.(2016). FullHand: Markerless Skeleton-based Tracking for Free-Hand Interaction (MPI-I-2016-4-002). Saarbrücken: Max-Planck-Institut für Informatik.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-002B-7456-7
Zusammenfassung
This paper advances a novel markerless hand tracking method for interactive applications. FullHand uses input from RGB and depth cameras in a desktop setting. It combines, in a voting scheme, a discriminative, part-based pose retrieval with a generative pose estimation method based on local optimization. We develop this approach to enable: (1) capturing hand articulations with high number of degrees of freedom, including the motion of all fingers, (2) sufficient precision, shown in a dataset of user-generated gestures, and (3) a high framerate of 50 fps for one hand. We discuss the design of free-hand interactions with the tracker and present several demonstrations ranging from simple (few DOFs) to complex (finger individuation plus global hand motion), including mouse operation, a first-person shooter and virtual globe navigation. A user study on the latter shows that free-hand interactions implemented for the tracker can equal mouse-based interactions in user performance.