Extended abstract: Efficient image processing for continuous mobile vision

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Vision algorithms have enabled our camera-equipped devices to perform powerful tasks, including barcode scanning, object detection,text recognition, and face identification. Unfortunately,these tasks require significant energy to capture,process, and analyze images through the image sensor (imager),image signal processor (ISP), and application processor,limiting the longevity of such applications to short-term, on-demand use. We propose the investigation of an image processing paradigm that uses vision task information to optimize the energy cost of the image capture pipeline. Copyright is held by the owner/author(s). Publication rights licensed to ACM.

Original languageEnglish (US)
Title of host publicationMobiSys 2014 - PhD Forum 2014
PublisherAssociation for Computing Machinery
Pages9-10
Number of pages2
ISBN (Print)9781450329408
DOIs
StatePublished - 2014
Externally publishedYes
Event2014 ACM MobiSys PhD Forum Workshop, PhD Forum 2014 - Bretton Woods, NH, United States
Duration: Jun 16 2014Jun 16 2014

Other

Other2014 ACM MobiSys PhD Forum Workshop, PhD Forum 2014
CountryUnited States
CityBretton Woods, NH
Period6/16/146/16/14

Fingerprint

Image processing
Image sensors
Pipelines
Cameras
Scanning
Costs
Object detection

Keywords

  • Computer Vision
  • Energy Efficiency
  • Image Sensors
  • Image Signal Processing
  • Mobile Systems
  • Operating Systems

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

LiKamWa, R. (2014). Extended abstract: Efficient image processing for continuous mobile vision. In MobiSys 2014 - PhD Forum 2014 (pp. 9-10). Association for Computing Machinery. https://doi.org/10.1145/2611166.2611171

Extended abstract : Efficient image processing for continuous mobile vision. / LiKamWa, Robert.

MobiSys 2014 - PhD Forum 2014. Association for Computing Machinery, 2014. p. 9-10.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

LiKamWa, R 2014, Extended abstract: Efficient image processing for continuous mobile vision. in MobiSys 2014 - PhD Forum 2014. Association for Computing Machinery, pp. 9-10, 2014 ACM MobiSys PhD Forum Workshop, PhD Forum 2014, Bretton Woods, NH, United States, 6/16/14. https://doi.org/10.1145/2611166.2611171
LiKamWa R. Extended abstract: Efficient image processing for continuous mobile vision. In MobiSys 2014 - PhD Forum 2014. Association for Computing Machinery. 2014. p. 9-10 https://doi.org/10.1145/2611166.2611171
LiKamWa, Robert. / Extended abstract : Efficient image processing for continuous mobile vision. MobiSys 2014 - PhD Forum 2014. Association for Computing Machinery, 2014. pp. 9-10
@inproceedings{a08ff5be9757474bb9065819be797fce,
title = "Extended abstract: Efficient image processing for continuous mobile vision",
abstract = "Vision algorithms have enabled our camera-equipped devices to perform powerful tasks, including barcode scanning, object detection,text recognition, and face identification. Unfortunately,these tasks require significant energy to capture,process, and analyze images through the image sensor (imager),image signal processor (ISP), and application processor,limiting the longevity of such applications to short-term, on-demand use. We propose the investigation of an image processing paradigm that uses vision task information to optimize the energy cost of the image capture pipeline. Copyright is held by the owner/author(s). Publication rights licensed to ACM.",
keywords = "Computer Vision, Energy Efficiency, Image Sensors, Image Signal Processing, Mobile Systems, Operating Systems",
author = "Robert LiKamWa",
year = "2014",
doi = "10.1145/2611166.2611171",
language = "English (US)",
isbn = "9781450329408",
pages = "9--10",
booktitle = "MobiSys 2014 - PhD Forum 2014",
publisher = "Association for Computing Machinery",

}

TY - GEN

T1 - Extended abstract

T2 - Efficient image processing for continuous mobile vision

AU - LiKamWa, Robert

PY - 2014

Y1 - 2014

N2 - Vision algorithms have enabled our camera-equipped devices to perform powerful tasks, including barcode scanning, object detection,text recognition, and face identification. Unfortunately,these tasks require significant energy to capture,process, and analyze images through the image sensor (imager),image signal processor (ISP), and application processor,limiting the longevity of such applications to short-term, on-demand use. We propose the investigation of an image processing paradigm that uses vision task information to optimize the energy cost of the image capture pipeline. Copyright is held by the owner/author(s). Publication rights licensed to ACM.

AB - Vision algorithms have enabled our camera-equipped devices to perform powerful tasks, including barcode scanning, object detection,text recognition, and face identification. Unfortunately,these tasks require significant energy to capture,process, and analyze images through the image sensor (imager),image signal processor (ISP), and application processor,limiting the longevity of such applications to short-term, on-demand use. We propose the investigation of an image processing paradigm that uses vision task information to optimize the energy cost of the image capture pipeline. Copyright is held by the owner/author(s). Publication rights licensed to ACM.

KW - Computer Vision

KW - Energy Efficiency

KW - Image Sensors

KW - Image Signal Processing

KW - Mobile Systems

KW - Operating Systems

UR - http://www.scopus.com/inward/record.url?scp=84904347262&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84904347262&partnerID=8YFLogxK

U2 - 10.1145/2611166.2611171

DO - 10.1145/2611166.2611171

M3 - Conference contribution

AN - SCOPUS:84904347262

SN - 9781450329408

SP - 9

EP - 10

BT - MobiSys 2014 - PhD Forum 2014

PB - Association for Computing Machinery

ER -