Robust Camera Self-Calibration

The demands in camera self-calibration is very high but unfortunately, at the moment, there is no mature method has been found or developed so far.

In this research we aim to develop a robust camera self-calibration algorithm for general cameras, either using single or multiple view as the input. The camera model is restricted to be a pinhole camera which is supposed to be projective camera, including the smartphone cameras. As the first method in self-calibration was the Kruppa's equations which is worked based on the absolute conic, then the method that we are going to develop will first investigate the Kruppa's as the basic and for the better understanding of the problem.

The possibility of the algorithm to be used for stereo camera will also be investigated for the future use.

Stichworte

• Camera Self-Calibration

Publikationen

• Arash Shahbaz Badr, Luh Prapitasari and Rolf-Rainer Grigat : A SIFT_Based Feature Matching Algorithm Using Homography Estimation . In , Hrsg., . , Accepted at International Conference on Computer Vision Theory and Application (VISAPP) 2015 11-14 March 2015, Berlin-Germany , 2015.
• Luh Prapitasari und Rolf-Rainer Grigat: A Study of Kruppa's Equation for Camera Self-Calibration. In , Hrsg., . , International Conference on Machine Vision and Machine Learning (MVML'14), August 14-15 2014, Prague, Czech Republic, 2014.
• Luh Prapitasari und Rolf-Rainer Grigat: Image of The Absolute Conic: Where is it?. In , Hrsg., . , International Computer Vision Summer School (ICVSS 2014), July 13-19 2014, Sicily, Italy, 2014.