Synchronized dual camera vision system for locating and identify highly dynamic objects
This paper presents machine vision for locating and identifying 23 highly dynamic objects on 4.4 meters by 2.8 meters micro robot soccer playing field. The approach is based from the idea that the two camera vision subsystems should be synchronized and well informed in real time of the combined visi...
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oai:animorepository.dlsu.edu.ph:faculty_research-39082021-11-16T06:11:55Z Synchronized dual camera vision system for locating and identify highly dynamic objects Gunay, Noel S. Dadios, Elmer P. Vicerra, Ryan Rhay P. Bandala, Argel A. Gan Lim, Laurence A. This paper presents machine vision for locating and identifying 23 highly dynamic objects on 4.4 meters by 2.8 meters micro robot soccer playing field. The approach is based from the idea that the two camera vision subsystems should be synchronized and well informed in real time of the combined vision data and a selection of objects to track under each other's camera view. A measure of effectiveness on using incremental tracking for two-camera operation is developed and is used to evaluate the introduced approach through experimentation. A real-time visualization of the whole playfield containing the 22 micro robots and a golf ball is also provided for the system operator to validate the objects' actual poses with the vision system's measurements. Results show that the proposed technique is very fast, accurate, reliable, and robust to external disturbances. © 2014, Fuji Technology Press. All rights reserved. 2014-09-01T07:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/2909 Faculty Research Work Animo Repository Computer vision Real-time control Robotics in sports Manufacturing Mechanical Engineering |
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Computer vision Real-time control Robotics in sports Manufacturing Mechanical Engineering Gunay, Noel S. Dadios, Elmer P. Vicerra, Ryan Rhay P. Bandala, Argel A. Gan Lim, Laurence A. Synchronized dual camera vision system for locating and identify highly dynamic objects |
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This paper presents machine vision for locating and identifying 23 highly dynamic objects on 4.4 meters by 2.8 meters micro robot soccer playing field. The approach is based from the idea that the two camera vision subsystems should be synchronized and well informed in real time of the combined vision data and a selection of objects to track under each other's camera view. A measure of effectiveness on using incremental tracking for two-camera operation is developed and is used to evaluate the introduced approach through experimentation. A real-time visualization of the whole playfield containing the 22 micro robots and a golf ball is also provided for the system operator to validate the objects' actual poses with the vision system's measurements. Results show that the proposed technique is very fast, accurate, reliable, and robust to external disturbances. © 2014, Fuji Technology Press. All rights reserved. |
format |
text |
author |
Gunay, Noel S. Dadios, Elmer P. Vicerra, Ryan Rhay P. Bandala, Argel A. Gan Lim, Laurence A. |
author_facet |
Gunay, Noel S. Dadios, Elmer P. Vicerra, Ryan Rhay P. Bandala, Argel A. Gan Lim, Laurence A. |
author_sort |
Gunay, Noel S. |
title |
Synchronized dual camera vision system for locating and identify highly dynamic objects |
title_short |
Synchronized dual camera vision system for locating and identify highly dynamic objects |
title_full |
Synchronized dual camera vision system for locating and identify highly dynamic objects |
title_fullStr |
Synchronized dual camera vision system for locating and identify highly dynamic objects |
title_full_unstemmed |
Synchronized dual camera vision system for locating and identify highly dynamic objects |
title_sort |
synchronized dual camera vision system for locating and identify highly dynamic objects |
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Animo Repository |
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2014 |
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https://animorepository.dlsu.edu.ph/faculty_research/2909 |
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