A real-time video processing implementation with massively parallel computation support

Woosuk Shin, Mingyu Kim, Sukjun Park, Nakhoon Baek

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Recently, performance of mobile device's processor has advanced dramatically. There are many researches to utilize the processor computing ability to maximize application performance. In the field of augmented reality (AR), video stream processing is an application that requires large amount of computing powers, from the real-time processing point of view. However, due to nature of mobile platforms, unnecessary overheads should be minimized to acquire higher performance. In this paper, we introduce OpenCL based video frame segmentation to minimize unnecessary overhead in video processing applications, with dynamically changing the local work group size. Our prototype system show at most 2.3 times speed-up compared to well-known, de-facto image processing library OpenCV.

Original languageEnglish
Title of host publication2020 International Conference on Electronics, Information, and Communication, ICEIC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728162898
DOIs
StatePublished - Jan 2020
Event2020 International Conference on Electronics, Information, and Communication, ICEIC 2020 - Barcelona, Spain
Duration: 19 Jan 202022 Jan 2020

Publication series

Name2020 International Conference on Electronics, Information, and Communication, ICEIC 2020

Conference

Conference2020 International Conference on Electronics, Information, and Communication, ICEIC 2020
Country/TerritorySpain
CityBarcelona
Period19/01/2022/01/20

Keywords

  • Massively parallel processing
  • Mobile computing
  • Real-time video processing

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