demonstration

Scaling virtual camera services to a large number of users

Authors:

Vamsidhar Reddy Gaddam,

Ragnar Langseth,

Håkon Kvale Stensland,

Carsten Griwodz,

Pål Halvorsen,

Dag JohansenAuthors Info & Claims

MMSys '15: Proceedings of the 6th ACM Multimedia Systems Conference

Pages 93 - 96

https://doi.org/10.1145/2713168.2713189

Published: 18 March 2015 Publication History

Abstract

By processing video footage from a camera array, one can easily make wide-field-of-view panorama videos. From the single panorama video, one can further generate multiple virtual cameras supporting personalized views to a large number of users based on only the few physical cameras in the array. However, giving personalized services to large numbers of users potentially introduces both bandwidth and processing bottlenecks, depending on where the virtual camera is processed.

In this demonstration, we present a system that address the large cost of transmitting entire panorama video to the end-user where the user creates the virtual views on the client device. Our approach is to divide the panorama into tiles, each encoded in multiple qualities. Then, the panorama video tiles are retrieved by the client in a quality (and thus bit rate) depending on where the virtual camera is pointing, i.e., the video quality of the tile changes dynamically according to the user interaction. Our initial experiments indicate that there is a large potential of saving bandwidth on the cost of trading quality of in areas of the panorama frame not used for the extraction of the virtual view.

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Cited By

Carrillo HQuiroga JZapata LMaldonado E(2022)Automatic football video production system with edge processingMachine Vision and Applications10.1007/s00138-022-01283-033:2Online publication date: 21-Feb-2022
https://doi.org/10.1007/s00138-022-01283-0
Carlsson NEager DKrishnamoorthi VPolishchuk T(2017)Optimized Adaptive Streaming of Multi-video Stream BundlesIEEE Transactions on Multimedia10.1109/TMM.2017.267341219:7(1637-1653)Online publication date: 15-Jun-2017
https://dl.acm.org/doi/10.1109/TMM.2017.2673412

Index Terms

Scaling virtual camera services to a large number of users
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision

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Information & Contributors

Information

Published In

cover image ACM Conferences

MMSys '15: Proceedings of the 6th ACM Multimedia Systems Conference

March 2015

277 pages

ISBN:9781450333511

DOI:10.1145/2713168

General Chair:
Wei Tsang Ooi
National University of Singapore, Singapore
,
Program Chairs:
Wu-chi Feng
Portland State University
,
Feng Liu
Portland State University

Copyright © 2015 Owner/Author.

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 March 2015

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Author Tags

Qualifiers

Demonstration

Funding Sources

Norwegian Research Council

Conference

MMSys '15

Sponsor:

MMSys '15: Multimedia Systems Conference 2015

March 18 - 20, 2015

Oregon, Portland

Acceptance Rates

MMSys '15 Paper Acceptance Rate 12 of 41 submissions, 29%;

Overall Acceptance Rate 176 of 530 submissions, 33%

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Cited By

Carrillo HQuiroga JZapata LMaldonado E(2022)Automatic football video production system with edge processingMachine Vision and Applications10.1007/s00138-022-01283-033:2Online publication date: 21-Feb-2022
https://doi.org/10.1007/s00138-022-01283-0
Carlsson NEager DKrishnamoorthi VPolishchuk T(2017)Optimized Adaptive Streaming of Multi-video Stream BundlesIEEE Transactions on Multimedia10.1109/TMM.2017.267341219:7(1637-1653)Online publication date: 15-Jun-2017
https://dl.acm.org/doi/10.1109/TMM.2017.2673412

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