Accelerated shadow detection and removal method

Edward Richter, Ryan Raettig, Joshua Mack, Spencer Valancius, Burak Unal, Ali Akoglu

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

1 Scopus citations

Abstract

Shadows can have a negative effect on the ability of computer vision techniques for object detection, tracking, and recognition. Therefore, ability to remove shadows and byproducts of illumination is an important problem to enable effective object recognition actions. As applications move into levels of higher information extraction and higher required processing speeds, efficient and sophisticated shadow detection and removal becomes even more necessary. In this study we propose a shadow removal method, parallelize using a Tesla P100 GPU, and achieve a speedup of 21.67× on an 18 megapixel (MP) resolution image compared to the same method implemented in Matlab.

Original languageEnglish (US)
Title of host publication16th ACS/IEEE International Conference on Computer Systems and Applications, AICCSA 2019
PublisherIEEE Computer Society
ISBN (Electronic)9781728150529
DOIs
StatePublished - Nov 2019
Event16th ACS/IEEE International Conference on Computer Systems and Applications, AICCSA 2019 - Abu Dhabi, United Arab Emirates
Duration: Nov 3 2019Nov 7 2019

Publication series

NameProceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA
Volume2019-November
ISSN (Print)2161-5322
ISSN (Electronic)2161-5330

Conference

Conference16th ACS/IEEE International Conference on Computer Systems and Applications, AICCSA 2019
Country/TerritoryUnited Arab Emirates
CityAbu Dhabi
Period11/3/1911/7/19

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Signal Processing
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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