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 Energy, Geoscience, Infrastructure and Society

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

25 Citations (Scopus)

110 Downloads (Pure)

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	IEEE
Number of pages	8
ISBN (Print)	978-1-4244-5497-6
DOIs	https://doi.org/10.1109/WACV.2009.5403103
Publication status	Published - 2009
Event	IEEE Workshop on Applications of Computer Vision (WACV) 2009 - Snowbird, United States Duration: 7 Dec 2009 → 8 Dec 2009

Conference

Conference	IEEE Workshop on Applications of Computer Vision (WACV) 2009
Country/Territory	United States
City	Snowbird
Period	7/12/09 → 8/12/09

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10.1109/WACV.2009.5403103

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@inproceedings{e981f8668a0147a1ae80c57e522b2b21,

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 = "2009",

doi = "10.1109/WACV.2009.5403103",

language = "English",

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

publisher = "IEEE",

address = "United States",

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

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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 - 2009

Y1 - 2009

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 - IEEE

T2 - IEEE Workshop on Applications of Computer Vision (WACV) 2009

Y2 - 7 December 2009 through 8 December 2009

ER -

Haarlet-based hand gesture recognition for 3D interaction

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