Synchronized Dual Camera Vision System for Locating and Identify Highly Dynamic Objects
Noel S. Gunay, Elmer P. Dadios, Ryan Rhay P. Vicerra,
Argel A. Bandala, and Laurence A. Gan Lim
De La Salle University, 2401 Taft Ave., Manila, 1004 Philippines
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.
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