Poster: Retrofitting computer vision libraries for concurrent support on mobile devices

Robert LiKamWa, Eddie Reyes, Lin Zhong

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

1 Scopus citations

Abstract

While computer vision algorithms and libraries have enabled and accelerated the adoption of vision processing into mobile and wearable applications, vision is a resource-hungry operation, and is thus not efficient enough to run on multiple applications simultaneously. However, we observe that many vision algorithms share identical sets of frames and features to perform their analyses, computed from the same library calls. Leveraging this observation, we design a split-process architecture to retrofit existing vision libraries to allow applications to transparently share the computational, memory, and energy overhead of vision processing. Copyright

Original languageEnglish (US)
Title of host publicationMobiCom 2014 - Proceedings of the 20th Annual
PublisherAssociation for Computing Machinery
Pages387-389
Number of pages3
ISBN (Electronic)9781450327831
DOIs
StatePublished - Sep 7 2014
Externally publishedYes
Event20th ACM Annual International Conference on Mobile Computing and Networking, MobiCom 2014 - Maui, United States
Duration: Sep 7 2014Sep 11 2014

Publication series

NameProceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM

Other

Other20th ACM Annual International Conference on Mobile Computing and Networking, MobiCom 2014
CountryUnited States
CityMaui
Period9/7/149/11/14

Keywords

  • Remote execution
  • Shared memory management
  • Split-process

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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