Stream processing of integral images for real-time object detection

Chris Messom*, Andre Barczak

*Corresponding author for this work

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

14 Citations (Scopus)

Abstract

This paper presents the design and evaluation of the stream processing implementation of the Integral Image algorithm. The Integral Image is a key component of many image processing algorithms in particular the Haar-like feature based systems. Modern GPUs provide a large number of processors with a peak floating point performance that is significantly higher than current general CPUs. This results in significant performance improvement when the Integral Image calculation for large input images is offloaded onto the GPU of the system.

Original languageEnglish
Title of host publicationProceedings - 9th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2008
EditorsZhiyi Huang, Zhiwei Xu, Nathan Rountree, Laurent Lefevre, Hong Shen, John Hine, Yi Pan
PublisherIEEE
Pages405-412
Number of pages8
ISBN (Print)9780769534435
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event9th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2008 - Dunedin, Otago, New Zealand
Duration: 1 Dec 20084 Dec 2008
Conference number: 9th

Publication series

NameParallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings

Conference

Conference9th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2008
Abbreviated titlePDCAT
Country/TerritoryNew Zealand
CityDunedin, Otago
Period1/12/084/12/08

Fingerprint

Dive into the research topics of 'Stream processing of integral images for real-time object detection'. Together they form a unique fingerprint.

Cite this