Haarlet-based hand gesture recognition for 3D interaction

Michael Van den Bergh; Frédéric Bosché; E Koller-Meier; Luc Van Gool

doi:10.1109/WACV.2009.5403103

Haarlet-based hand gesture recognition for 3D interaction

Michael Van den Bergh, Frédéric Bosché, E Koller-Meier, Luc Van Gool

School of Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper presents a system to manipulate 3D objectsor navigate through 3D models by detecting the gesturesand the movements of the hands of a user in front of a cameramounted on top of a screen. This paper more particularlyintroduces an improved skin color segmentation algorithmwhich combines an online and an offline model; anda Haarlet-based hand gesture recognition system, wherethe Haarlets are trained based on Average NeighborhoodMargin Maximization (ANMM). The result is a real-timemarker-less interaction system which is applied to two applications,one for manipulating 3D objects, and the otherfor navigating through a 3D model.

Original language	English
Title of host publication	2009 Workshop on Applications of Computer Vision (WACV)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
ISBN (Print)	978-1-4244-5497-6
DOIs	https://doi.org/10.1109/WACV.2009.5403103
Publication status	Published - 2 Feb 2010
Event	2009 Workshop on Applications of Computer Vision - Snowbird, United States Duration: 7 Dec 2009 → 8 Dec 2009

Workshop

Workshop	2009 Workshop on Applications of Computer Vision
Abbreviated title	WACV
Country/Territory	United States
City	Snowbird
Period	7/12/09 → 8/12/09

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10.1109/WACV.2009.5403103

Cite this

@inproceedings{e0e7a21d4b244acca53cbf6d3a1075d5,

title = "Haarlet-based hand gesture recognition for 3D interaction",

abstract = "This paper presents a system to manipulate 3D objectsor navigate through 3D models by detecting the gesturesand the movements of the hands of a user in front of a cameramounted on top of a screen. This paper more particularlyintroduces an improved skin color segmentation algorithmwhich combines an online and an offline model; anda Haarlet-based hand gesture recognition system, wherethe Haarlets are trained based on Average NeighborhoodMargin Maximization (ANMM). The result is a real-timemarker-less interaction system which is applied to two applications,one for manipulating 3D objects, and the otherfor navigating through a 3D model.",

author = "{Van den Bergh}, Michael and Fr{\'e}d{\'e}ric Bosch{\'e} and E Koller-Meier and {Van Gool}, Luc",

year = "2010",

month = feb,

day = "2",

doi = "10.1109/WACV.2009.5403103",

language = "English",

isbn = "978-1-4244-5497-6",

booktitle = "2009 Workshop on Applications of Computer Vision (WACV)",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "2009 Workshop on Applications of Computer Vision , WACV ; Conference date: 07-12-2009 Through 08-12-2009",

}

Van den Bergh, M, Bosché, F, Koller-Meier, E & Van Gool, L 2010, Haarlet-based hand gesture recognition for 3D interaction. in 2009 Workshop on Applications of Computer Vision (WACV). Institute of Electrical and Electronics Engineers (IEEE), 2009 Workshop on Applications of Computer Vision , Snowbird, Utah, United States, 7/12/09. https://doi.org/10.1109/WACV.2009.5403103

TY - GEN

T1 - Haarlet-based hand gesture recognition for 3D interaction

AU - Van den Bergh, Michael

AU - Bosché, Frédéric

AU - Koller-Meier, E

AU - Van Gool, Luc

PY - 2010/2/2

Y1 - 2010/2/2

N2 - This paper presents a system to manipulate 3D objectsor navigate through 3D models by detecting the gesturesand the movements of the hands of a user in front of a cameramounted on top of a screen. This paper more particularlyintroduces an improved skin color segmentation algorithmwhich combines an online and an offline model; anda Haarlet-based hand gesture recognition system, wherethe Haarlets are trained based on Average NeighborhoodMargin Maximization (ANMM). The result is a real-timemarker-less interaction system which is applied to two applications,one for manipulating 3D objects, and the otherfor navigating through a 3D model.

AB - This paper presents a system to manipulate 3D objectsor navigate through 3D models by detecting the gesturesand the movements of the hands of a user in front of a cameramounted on top of a screen. This paper more particularlyintroduces an improved skin color segmentation algorithmwhich combines an online and an offline model; anda Haarlet-based hand gesture recognition system, wherethe Haarlets are trained based on Average NeighborhoodMargin Maximization (ANMM). The result is a real-timemarker-less interaction system which is applied to two applications,one for manipulating 3D objects, and the otherfor navigating through a 3D model.

U2 - 10.1109/WACV.2009.5403103

DO - 10.1109/WACV.2009.5403103

M3 - Conference contribution

SN - 978-1-4244-5497-6

BT - 2009 Workshop on Applications of Computer Vision (WACV)

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 2009 Workshop on Applications of Computer Vision

Y2 - 7 December 2009 through 8 December 2009

ER -

Haarlet-based hand gesture recognition for 3D interaction

Abstract

Workshop

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