@inproceedings {23526,
	title = {Online Re-calibration for Robust 3D Measurement Using Single Camera-PantoInspect Train Monitoring System},
	journal = {Proceedings of the International Conference on Computer Vision Systems (ICVS) - Lecture Notes in Computer Science Volume 9163},
	year = {2015},
	publisher = {Lecture Notes in Computer Science, Springer.Verlag},
	abstract = {Vision-based inspection systems measures defects accurately with the help of a checkerboard calibration (CBC) method. However, the 3D measurements of such systems are prone to errors, caused by physical misalignment of the object-of-interest and noisy image data. The PantoInspect Train Monitoring System (PTMS), is one such system that inspects defects on pantographs mounted on top of the electric trains. In PTMS, the measurement errors can compromise railway safety. Although this problem can be solved by re-calibrating the cameras, the process involves manual intervention leading to large servicing times. Therefore, in this paper, we propose Feature Based Calibration (FBC) in place of CBC, to cater an obvious need for online re-calibration that enhances the usability of the system. FBC involves feature extraction, pose estimation, back-projection of defect points and estimation of 3D measurements. We explore four state-of-the-art pose estimation algorithms in FBC using very few feature points. This paper evaluates and discusses the performance of FBC and its robustness against practical problems, in comparison to CBC. As a result, we identify the best FBC algorithm type and operational scheme for PTMS. In conclusion, we show that, by adopting FBC in PTMS and other related 3D systems, better performance and robustness can be achieved compared to CBC.\&nbsp;},
	doi = {10.1007/978-3-319-20904-3_45},
	author = {Dwarakanath, Deepak and Griwodz, Carsten and Halvorsen, P{\r a}l and Lildballe, Jacob}
}
@inbook {19152,
	title = {Study the Effects of Camera Misalignment on 3D Measurements for Efficient Design of Vision-Based Inspection Systems},
	booktitle = {Artificial Intelligence: Methods and Applications},
	series = {Lecture Notes in Computer Science},
	volume = {8445},
	year = {2014},
	pages = {150{\textendash}163},
	publisher = {Springer},
	organization = {Springer},
	address = {N/A},
	keywords = {Camera calibration, Camera misalignment and Regression models, Vision based inspection systems},
	isbn = {978-3-319-07063-6},
	doi = {10.1007/978-3-319-07064-3\_13},
	url = {http://dx.doi.org/10.1007/978-3-319-07064-3\_13},
	author = {Dwarakanath, Deepak and Griwodz, Carsten and Halvorsen, P{\r a}l and Lildballe, Jacob},
	editor = {Blekas, Konstantinos and Likas, Aristidis and Kalles, Dimitris}
}
@inproceedings {Simula.simula.2656,
	title = {Study the Effects of Camera Misalignment on 3D Measurements for Efficient Design of Vision-Based Inspection Systems},
	journal = {8th Hellenic Conference on Artificial Intelligence (SETN 2014)},
	year = {2014},
	month = {Mary},
	publisher = {Springer-Verlag},
	type = {Annual},
	abstract = {Vision based inspection systems for 3D measurements using single camera, are extensively used in several industries, today. Due to transportation and/or servicing of these systems, the camera in this system is prone to mis-alignment from its original position. In such situations, although a high quality calibration exists, the accuracy of 3D measurement is affected. In this paper, we propose a statistical tool or methodology which involves. a) Studying the significance of the effects of 3d measurements errors due to camera mis-alignment. b) Modelling the error data using regression models. c) Deducing expressions to determine tolerances of camera mis-alignment for an acceptable inaccuracy of the system. This tool can be used by any 3D measuring system using single camera. Resulting tolerances can be directly used for mechanical design of camera placement in the vision based inspection systems.},
	keywords = {Workshop},
	author = {Dwarakanath, Deepak and Griwodz, Carsten and Halvorsen, P{\r a}l and Lildballe, Jacob},
	editor = {Likas, Aristidis and Blekas, Konstantinos and Kalles, Dimitris}
}
