Skip to search boxSkip to navigationSkip to main content

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

Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution

Publication metrics

Metrics

Scopus
Citations
SciVal
Citations
1
SciVal
Author count
6
SciVal
Paper percentile
28

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.

Publication Information

Output type

Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution

Original language

English

Pages from-to (Number of pages)

Pages 519-524 (6 pages)

Publication milestones

  • Published - 02/07/2017

Publication status

Published - 02/07/2017

Publisher

IEEE Computer Society, United States

Publication series

  • Publication series name: International Conference on Advanced Mechatronic Systems, ICAMechS
    ISSN (Print): 2325-0682
    ISSN (Electronic): 2325-0690
    Volume: 2017-December
9781538626023

ISBN (Electronic)

978-153862602-3

Publication IDs

  • Scopus: 85046679575

Host publication title

2017 International Conference on Advanced Mechatronic Systems, ICAMechS 2017

Related Event

Title

International Conference on Advanced Mechatronic Systems, ICAMechS

Event type

Conference

Date

14/03/2018

Funding Details

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.