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Wiizards: 3D gesture recognition for game play input

Authors:

Louis Kratz,

Matthew Smith,

Frank J. LeeAuthors Info & Claims

Future Play '07: Proceedings of the 2007 conference on Future Play

Pages 209 - 212

https://doi.org/10.1145/1328202.1328241

Published: 14 November 2007 Publication History

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Abstract

Gesture based input is an emerging technology gaining widespread popularity in interactive entertainment. The use of gestures provides intuitive and natural input mechanics for games, presenting an easy to learn yet richly immersive experience. In Wiizards, we explore the use of 3D accelerometer gestures in a multiplayer, zero sum game. Hidden Markov models are constructed for gesture recognition, providing increased flexibility and fluid tolerance. Users can strategically effect the outcome via combinations of gestures with limitless scalability.

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Qi TCibrian FRaswan MKay TCamarillo-Abad HWen Y(2024)Toward Intuitive 3D Interactions in Virtual Reality: A Deep Learning- Based Dual-Hand Gesture Recognition ApproachIEEE Access10.1109/ACCESS.2024.340029512(67438-67452)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3400295
Raees MUllah SRehman IAzhar M(2021)Thumb Inclination-Based Manipulation and Exploration, a Machine Learning Based Interaction Technique for Virtual EnvironmentsMehran University Research Journal of Engineering and Technology10.22581/muet1982.2102.1040:2(358-370)Online publication date: 1-Apr-2021
https://doi.org/10.22581/muet1982.2102.10
Carrara FElias PSedmidubsky JZezula P(2019)LSTM-based real-time action detection and prediction in human motion streamsMultimedia Tools and Applications10.1007/s11042-019-07827-3Online publication date: 18-Jun-2019
https://doi.org/10.1007/s11042-019-07827-3
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Wiizards: 3D gesture recognition for game play input

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Published In

Future Play '07: Proceedings of the 2007 conference on Future Play

November 2007

279 pages

ISBN:9781595939432

DOI:10.1145/1328202

Conference Chairs:
Bill Kapralos
University of Ontario Institute of Technology
,
Mike Katchabaw
University of Western Ontario
,
Jay Rajnovich
Algoma U

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

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Published: 14 November 2007

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November 14 - 17, 2007

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Qi TCibrian FRaswan MKay TCamarillo-Abad HWen Y(2024)Toward Intuitive 3D Interactions in Virtual Reality: A Deep Learning- Based Dual-Hand Gesture Recognition ApproachIEEE Access10.1109/ACCESS.2024.340029512(67438-67452)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3400295
Raees MUllah SRehman IAzhar M(2021)Thumb Inclination-Based Manipulation and Exploration, a Machine Learning Based Interaction Technique for Virtual EnvironmentsMehran University Research Journal of Engineering and Technology10.22581/muet1982.2102.1040:2(358-370)Online publication date: 1-Apr-2021
https://doi.org/10.22581/muet1982.2102.10
Carrara FElias PSedmidubsky JZezula P(2019)LSTM-based real-time action detection and prediction in human motion streamsMultimedia Tools and Applications10.1007/s11042-019-07827-3Online publication date: 18-Jun-2019
https://doi.org/10.1007/s11042-019-07827-3
Miao YWang LXie CZhang B(2017)Gesture Recognition Based on Deep Belief NetworksBiometric Recognition10.1007/978-3-319-69923-3_47(439-446)Online publication date: 20-Oct-2017
https://doi.org/10.1007/978-3-319-69923-3_47
Jang MKim JSeo YYang H(2015)Adaptive gesture tracking and recognition using acceleration sensors for a mobile deviceInternational Journal of Wireless and Mobile Computing10.1504/IJWMC.2015.0686248:2(183-193)Online publication date: 1-Apr-2015
https://dl.acm.org/doi/10.1504/IJWMC.2015.068624
Henschke MGedeon TJones R(2015)Touchless Gestural Interaction with Wizard-of-OzProceedings of the Annual Meeting of the Australian Special Interest Group for Computer Human Interaction10.1145/2838739.2838792(207-211)Online publication date: 7-Dec-2015
https://dl.acm.org/doi/10.1145/2838739.2838792
Nogueira PTeófilo LSilva P(2015)Multi-modal natural interaction in game design: a comparative analysis of player experience in a large scale role-playing gameJournal on Multimodal User Interfaces10.1007/s12193-014-0172-19:2(105-119)Online publication date: 22-Jan-2015
https://doi.org/10.1007/s12193-014-0172-1
Whitehead A(2014)Gesture Recognition with Accelerometers for Game Controllers, Phones and WearablesGSTF Journal on Computing (JoC)10.7603/s40601-013-0042-93:4Online publication date: 28-May-2014
https://doi.org/10.7603/s40601-013-0042-9
Teófilo LNogueira PSilva P(2013)GEMINI: A Generic Multi-Modal Natural Interface Framework for VideogamesAdvances in Information Systems and Technologies10.1007/978-3-642-36981-0_81(873-884)Online publication date: 2013
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Boyali AKavakli M(2012)A robust gesture recognition algorithm based on Sparse Representation, random projections and Compressed Sensing2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA)10.1109/ICIEA.2012.6360730(243-249)Online publication date: Jul-2012
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Device agnostic 3D gesture recognition using hidden Markov models

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Playability: analysing user experience in video games

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