abstract

Gesture-based Sound Localization and Manipulation

Authors:

Shashank Ranjan,

Kyla McMullenAuthors Info & Claims

SUI '15: Proceedings of the 3rd ACM Symposium on Spatial User Interaction

Page 131

https://doi.org/10.1145/2788940.2794364

Published: 08 August 2015 Publication History

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Abstract

With current advancements in computer vision depth sensing technologies, gestures provide a new means of computer interaction. 3D audio research has gained significant ground in accurately localizing sound in 3D space, but not much work has been conducted relating to modes of user interaction in such applications. In this paper, gestures are used as a more natural way of interacting with 3D spatial audio applications, specifically for the localization and manipulation of sound sources.

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References

[1]

Fan, X., Essl, G. "Air Violin: A Body-centric Style Musical Instrument" In Proceedings of the International Conference on New Interfaces for Musical Expression (NIME), Daejeon + Seoul, South Korea, p.65--67, 2013.

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[2]

Matti Niinimäki and Koray Tahiroglu. 2012. AHNE: a novel interface for spatial interaction. In CHI '12 Extended Abstracts on Human Factors in Computing Systems (CHI EA '12). ACM, New York, NY, USA, 1031--1034.

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Index Terms

Gesture-based Sound Localization and Manipulation
1. Human-centered computing
  1. Human computer interaction (HCI)

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Information & Contributors

Information

Published In

SUI '15: Proceedings of the 3rd ACM Symposium on Spatial User Interaction

August 2015

152 pages

ISBN:9781450337038

DOI:10.1145/2788940

General Chair:
Amy Banic
University of Wyoming, USA
,
Program Chairs:
Evan Suma
University of Southern California, USA
,
Frank Steinicke
University of Hamburg, Germany
,
Wolfgang Stuerzlinger
Simon Fraser University, Canada

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 August 2015

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SUI '15

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SUI '15: Symposium on Spatial User Interaction

August 8 - 9, 2015

California, Los Angeles, USA

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SUI '15 Paper Acceptance Rate 17 of 48 submissions, 35%;

Overall Acceptance Rate 86 of 279 submissions, 31%

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Index Terms

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