Performance Analysis of Computer Vision with Machine Learning Algorithms on Raspberry Pi 3

Kevin Worsley, Anas Salah Eddin, Jinjun Xiong, Wen mei Hwu, Mohamed El-Hadedy

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


Computer vision is a dynamic field, with many applications in a wide variety of industries. Choosing a platform to deploy computer vision algorithms is a complex task, with a massive amount of choice, varying in operating system, computing power, and physical size. This paper aims to measure common computer vision algorithms on a Raspberry Pi 3, helping to clarify some performance measurements and provide a clearer image of the Raspberry Pi’s viability for common computer vision operations, as well as recommend some platforms for specific algorithms.

Original languageEnglish (US)
Title of host publicationProceedings of the Future Technologies Conference, FTC 2020, Volume 1
EditorsKohei Arai, Supriya Kapoor, Rahul Bhatia
Number of pages17
ISBN (Print)9783030631277
StatePublished - 2021
EventFuture Technologies Conference, FTC 2020 - San Francisco, United States
Duration: Nov 5 2020Nov 6 2020

Publication series

NameAdvances in Intelligent Systems and Computing
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365


ConferenceFuture Technologies Conference, FTC 2020
Country/TerritoryUnited States
CitySan Francisco


  • Computer vision
  • Face detection
  • Haar
  • Object detection
  • Performance
  • Raspberry Pi 3
  • YOLO
  • dlib

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)


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