Robust estimation of camera parameters using combinatorial optimization
CGIM '07 Proceedings of the Ninth IASTED International Conference on Computer Graphics and Imaging
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This paper proposes two indicators for predicting the quality of camera model parameters from a set of input images. The first indicator is based on the acutance. It can quickly indicate static or motion blur during image capture and correlates well with the 3D reconstruction error when using stereo cameras. The second indicator provides the overall distribution of control points in a set of input images. Although the importance of covering the entire field of view is verified, the spatial distribution of control points need not be uniform. The analysis is supported by experiments with mono and stereo cameras calibrated using both a low cost planar and a high quality 3D target.