A comparative review of camera calibrating methods with accuracy evaluation
By Joaquim Salvi, Xavier Armangué, Joan Batlle. Pattern Recognition, 2002
584 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Geology, Mechanical Engineering
View Paper: https://www.semanticscholar.org/paper/902fd5edaa1298398bacec6e3e023a11e24b706c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- S. S. Gorthi
- Daniel F. García
- Nuria Rodríguez
- Íñigo Rodríguez
- Luis Pérez
- P. Rastogi
- Rubén Usamentiaga
In Geology
In Mechanical Engineering
Citations in the corpus
- Fringe projection techniques: Whither we are? (2010, methodology): “standard camera calibration techniques of the computer vision field [150, 151, 152].”
- Digital camera calibration methods: Considerations and comparisons (2006, unknown): “…& Förstner, 2004; Cronk et al., 2006), stability of parameters (Shortis & Beyer, 1997; Peipe & Stephani, 2003; Läbe & Förstner, 2004), behaviour of IO parameters (Wiley & Wong, 1995; Läbe & Förstner, 2004) and accuracy aspects (D’Apuzzo & Maas, 1999; Salvi et al., 2002; Fraser & Al-Ajlouni, 2006).”
- Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review (2016, background): “Given a point in the scene, its corresponding point in the image can be obtained by mathematical models [21].”
- Camera as the instrument: the rising trend of vision based measurement (2014, background): “A variety of techniques are already available for camera calibration [28] and more are being proposed in recent research [29].”