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Computer vision for package tracking on omnidirectional wheeled conveyor: Case study.
- Source :
-
Engineering Applications of Artificial Intelligence . Nov2022, Vol. 116, pN.PAG-N.PAG. 1p. - Publication Year :
- 2022
-
Abstract
- In this paper, a real-time camera tracking system for package transportation on omnidirectional wheeled conveyor is presented. The camera tracking system is integrated with a closed-loop controller for packages path planning. No additional sensors are used for the controller implementation, only a 2-D Camera. The package's position and orientation are detected by the camera tracking system in real-time. Two proposed systems are presented, System I is implemented using the conventional image processing technique threshold method while System II is implemented using computer vision. In System II, three computer vision models were evaluated: Detectron2 , YOLOv5 and Faster R-CNN. Experimental results in real-time show that System I have lower accuracy rate 85.7% compared to System II which reported 98% and 88.1% for YOLOv5 and Detectron2 , respectively. YOLOv5 reported the best results among the computer vision models with 1% missing rate, 45.5 FPS and average precision of 99.8%. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09521976
- Volume :
- 116
- Database :
- Academic Search Index
- Journal :
- Engineering Applications of Artificial Intelligence
- Publication Type :
- Academic Journal
- Accession number :
- 159981605
- Full Text :
- https://doi.org/10.1016/j.engappai.2022.105438