research-article

CAME: cloud-assisted motion estimation for mobile video compression and transmission

Authors:

Jiangchuan Liu,

Hongbo JiangAuthors Info & Claims

NOSSDAV '12: Proceedings of the 22nd international workshop on Network and Operating System Support for Digital Audio and Video

Pages 95 - 100

https://doi.org/10.1145/2229087.2229113

Published: 07 June 2012 Publication History

Abstract

Video streaming has become one of the most popular networked applications and, with the increased bandwidth and computation power of mobile devices, anywhere and anytime streaming has become a reality. Unfortunately, it remains a challenging task to compress high-quality video in real-time in such devices given the excessive computation and energy demands of compression. On the other hand, transmitting the raw video is simply unaffordable from both energy and bandwidth perspective.

In this paper, we propose CAME, a novel cloud-assisted video compression method for mobile devices. CAME leverages the abundant cloud server resources for motion estimation, which is known to be the most computation-intensive step in video compression, accounting for over 90% of the computation time. With CAME, a mobile device selects and uploads only the key information of each picture frame to cloud servers for mesh-based motion estimation, eliminating most of the local computation operations. We develop smart algorithms to identify the key mesh nodes, resulting in minimum distortion and data volume for uploading. Our simulation results demonstrate that CAME saves almost 30% energy for video compression and transmission.

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Cited By

Pattanayak SSingh AKhan S(2023)Camera to Cloud: A Robust Solution for Seamless Video Data Integration for OTT and Film production2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT56998.2023.10308167(1-5)Online publication date: 6-Jul-2023
https://doi.org/10.1109/ICCCNT56998.2023.10308167
Chatzopoulos DSucipto KKosta SHui P(2016)Video compression in the neighborhood: An opportunistic approach2016 IEEE International Conference on Communications (ICC)10.1109/ICC.2016.7511320(1-6)Online publication date: May-2016
https://doi.org/10.1109/ICC.2016.7511320
Dong YZhou LJin YWen Y(2015)Improving Energy Efficiency for Mobile Media Cloud via Virtual Machine ConsolidationMobile Networks and Applications10.1007/s11036-015-0595-220:3(370-379)Online publication date: 28-Apr-2015
https://doi.org/10.1007/s11036-015-0595-2
Show More Cited By

Index Terms

CAME: cloud-assisted motion estimation for mobile video compression and transmission
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
2. Networks
  1. Network types
    1. Mobile networks
    2. Wireless access networks

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Published In

cover image ACM Conferences

NOSSDAV '12: Proceedings of the 22nd international workshop on Network and Operating System Support for Digital Audio and Video

June 2012

116 pages

ISBN:9781450314305

DOI:10.1145/2229087

Program Chairs:
Baochun Li
University of Toronto, Canada
,
Shervin Shirmohammadi
University of Ottawa, Canada

Copyright © 2012 ACM.

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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SIGMM: ACM Special Interest Group on Multimedia

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SIGCOMM: ACM Special Interest Group on Data Communication

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 June 2012

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NOSSDAV '12

Sponsor:

SIGMM

NOSSDAV '12: Network and Operating System Support for Digital Audio and Video Workshop

June 7 - 8, 2012

Ontario, Toronto, Canada

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Overall Acceptance Rate 118 of 363 submissions, 33%

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Cited By

Pattanayak SSingh AKhan S(2023)Camera to Cloud: A Robust Solution for Seamless Video Data Integration for OTT and Film production2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT56998.2023.10308167(1-5)Online publication date: 6-Jul-2023
https://doi.org/10.1109/ICCCNT56998.2023.10308167
Chatzopoulos DSucipto KKosta SHui P(2016)Video compression in the neighborhood: An opportunistic approach2016 IEEE International Conference on Communications (ICC)10.1109/ICC.2016.7511320(1-6)Online publication date: May-2016
https://doi.org/10.1109/ICC.2016.7511320
Dong YZhou LJin YWen Y(2015)Improving Energy Efficiency for Mobile Media Cloud via Virtual Machine ConsolidationMobile Networks and Applications10.1007/s11036-015-0595-220:3(370-379)Online publication date: 28-Apr-2015
https://doi.org/10.1007/s11036-015-0595-2
Zhang LWang FLiu J(2014)Understand Instant Video Clip Sharing on Mobile PlatformsProceedings of Network and Operating System Support on Digital Audio and Video Workshop10.1145/2597176.2578278(85-90)Online publication date: 19-Mar-2014
https://dl.acm.org/doi/10.1145/2597176.2578278
Zhang LWang FLiu J(2014)Understand Instant Video Clip Sharing on Mobile PlatformsProceedings of Network and Operating System Support on Digital Audio and Video Workshop10.1145/2578260.2578278(85-90)Online publication date: 19-Mar-2014
https://dl.acm.org/doi/10.1145/2578260.2578278
(2014)Cloud-Assisted Smart Camera Networks for Energy-Efficient 3D Video StreamingComputer10.1109/MC.2014.11447:5(60-66)Online publication date: May-2014
https://doi.org/10.1109/MC.2014.114
Li ZDrew MLiu JLi ZDrew MLiu J(2014)Cloud Computing for Multimedia ServicesFundamentals of Multimedia10.1007/978-3-319-05290-8_19(645-674)Online publication date: 10-Apr-2014
https://doi.org/10.1007/978-3-319-05290-8_19
Ma XZhao YZhang LWang HPeng L(2013)When mobile terminals meet the cloud: computation offloading as the bridgeIEEE Network10.1109/MNET.2013.661611227:5(28-33)Online publication date: Sep-2013
https://doi.org/10.1109/MNET.2013.6616112

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