Solving the stereo matching problem using an embedded GPU for a real-Time application

Pedro Aguiar, Sebastien Varrier, Jorge Lozoya, Martha Lopez, Damien Koenig, Juan C. Tudon-Martinez

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

Abstract

General-purpose computing on graphics processing units (GPGPU) is used not only to offload the CPU from heavy computations but also to perform them faster than it is possible on CPUs. This is commonly referred as GPU acceleration and is an exercised area of study in the PC platform that has received very little attention on commodity embedded devices. Just as the PC GPU is being used to perform computations that would be impossible in terms of execution time for its accompanying CPU, the embedded GPU can accelerate computations normally done by the embedded CPU. This work presents an implementation of a factible, real-Time, GPU accelerated stereo matching solution using a Broadcom's VideoCore IV GPU (BCM2835 System on a Chip). Details include the delimitation process, design considerations and optimization techniques.

Original languageEnglish
Title of host publicationInternational Conference on Advanced Mechatronic Systems, ICAMechS
PublisherIEEE Computer Society
Pages519-524
Number of pages6
ISBN (Electronic)978-153862602-3
ISBN (Print)9781538626023
DOIs
Publication statusPublished - 14 Mar 2018
EventInternational Conference on Advanced Mechatronic Systems, ICAMechS -
Duration: 14 Mar 2018 → …

Publication series

NameInternational Conference on Advanced Mechatronic Systems, ICAMechS
Volume2017-December
ISSN (Print)2325-0682
ISSN (Electronic)2325-0690

Conference

ConferenceInternational Conference on Advanced Mechatronic Systems, ICAMechS
Period14/3/18 → …

Bibliographical note

Funding Information:
WebGL is another graphics API from the Khronos Group that is supported by major web browsers in both PC and mobile platforms. WebGL is described as “OpenGL ES 2.0 for the Web” by Khronos because of their vast similarities. Shaders written for WebGL are very likely to work without any modifications on OpenGL ES 2.0. Other GPU setup operations such as buffers, textures and framebuffers creation, deletion and binding are exactly the same. This similarity between APIs was exploited in this work to benchmark the proposed algorithm running on different embedded GPUs through WebGL.

Publisher Copyright:
© 2017 IEEE.

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Electrical and Electronic Engineering

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