Name
Abstract | ||
|---|---|---|
Robotic vision is widely used to provide feedback for the calibration and operation of autonomous robots. In many situations, the automation of the robot requires tracking one or more points of interest on the robot or in its surroundings. In this work, we developed and tested a camera-based vision system that can detect multiple points of interest and discriminate them into up to three groups. This is achieved by exploring the Red, Green, and Blue color layers in a single video feed. The experimental results show the proposed system's ability to accurately locate and distinguish three points of interest mounted on an industrial robot. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/EIT.2016.7535228 | 2016 IEEE International Conference on Electro Information Technology (EIT) |
Keywords | Field | DocType |
computer vision,robotic calibration,target tracking,signal modulation | Computer vision,Signal modulation,Machine vision,Computer graphics (images),Computer science,Automation,Industrial robot,Artificial intelligence,RGB color model,Point of interest,Robot,Calibration | Conference |
ISSN | ISBN | Citations |
2154-0357 | 978-1-4673-9986-9 | 0 |
PageRank | References | Authors |
0.34 | 7 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sami Khorbotly | 1 | 8 | 3.73 |
| John-david Yoder | 2 | 113 | 8.97 |
| Eric T. Baumgartner | 3 | 173 | 20.05 |
| Timothy R. Chaffin | 4 | 0 | 0.34 |