A robust and accurate color-based global vision recognition of highly dynamic objects in real time

A color-based global vision system used to recognize 23 highly dynamic objects of interest using a firewire camera mounted at about 2.7m above a 2.8m × 2.3m field is presented. The developed algorithm used to identify the eleven home robots which was first shown to work on a webcam implementation by...

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Main Authors: Gunay, Noel S., Dadios, Elmer P.
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Published: Animo Repository 2011
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/2935
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Institution: De La Salle University
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-39342021-11-17T02:06:12Z A robust and accurate color-based global vision recognition of highly dynamic objects in real time Gunay, Noel S. Dadios, Elmer P. A color-based global vision system used to recognize 23 highly dynamic objects of interest using a firewire camera mounted at about 2.7m above a 2.8m × 2.3m field is presented. The developed algorithm used to identify the eleven home robots which was first shown to work on a webcam implementation by the authors' previous work is further evaluated in this paper using more testing experiments like identifying the home robots under intentionally varied illumination, shadow influence, object rotation, fast motion, collision and prolonged system operation. It is found that despite the 2.08 pixels per centimeter ratio versus the 3.8 of the webcam implementation, the eleven home robots were still accurately identified in all of these experiments while also identifying the ball and the eleven opponent robots. © 2011 Asian Control Association. 2011-08-29T07:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/2935 Faculty Research Work Animo Repository Computer vision Robotics in sports Robots Computer Sciences Robotics
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
topic Computer vision
Robotics in sports
Robots
Computer Sciences
Robotics
spellingShingle Computer vision
Robotics in sports
Robots
Computer Sciences
Robotics
Gunay, Noel S.
Dadios, Elmer P.
A robust and accurate color-based global vision recognition of highly dynamic objects in real time
description A color-based global vision system used to recognize 23 highly dynamic objects of interest using a firewire camera mounted at about 2.7m above a 2.8m × 2.3m field is presented. The developed algorithm used to identify the eleven home robots which was first shown to work on a webcam implementation by the authors' previous work is further evaluated in this paper using more testing experiments like identifying the home robots under intentionally varied illumination, shadow influence, object rotation, fast motion, collision and prolonged system operation. It is found that despite the 2.08 pixels per centimeter ratio versus the 3.8 of the webcam implementation, the eleven home robots were still accurately identified in all of these experiments while also identifying the ball and the eleven opponent robots. © 2011 Asian Control Association.
format text
author Gunay, Noel S.
Dadios, Elmer P.
author_facet Gunay, Noel S.
Dadios, Elmer P.
author_sort Gunay, Noel S.
title A robust and accurate color-based global vision recognition of highly dynamic objects in real time
title_short A robust and accurate color-based global vision recognition of highly dynamic objects in real time
title_full A robust and accurate color-based global vision recognition of highly dynamic objects in real time
title_fullStr A robust and accurate color-based global vision recognition of highly dynamic objects in real time
title_full_unstemmed A robust and accurate color-based global vision recognition of highly dynamic objects in real time
title_sort robust and accurate color-based global vision recognition of highly dynamic objects in real time
publisher Animo Repository
publishDate 2011
url https://animorepository.dlsu.edu.ph/faculty_research/2935
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