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Information Thoretic Criterion (AIC) and Camera Calibration

Information Thoretic Criterion (AIC) and Camera Calibration. G. Wei, K. Arbter, G. Hirzinger, “Active self-calibration of robotic eyes and hand-eye relationships with model identification,” IEEE Transaction Robotics and Automation, vol. 14(1), pp. 158-166, Feb. 1998.

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Information Thoretic Criterion (AIC) and Camera Calibration

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  1. Information Thoretic Criterion (AIC) and Camera Calibration

  2. G. Wei, K. Arbter, G. Hirzinger, “Active self-calibration of robotic eyes and hand-eye relationships with model identification,” IEEE Transaction Robotics and Automation, vol. 14(1), pp. 158-166, Feb. 1998. • Statistical inference based on Fisher’s distribution. • Select the best model to describe a problem while minimizing the number of parameters. Increase the reliability of the estimated parameters. • Avoid over-parameterization which can increase variance. • Three hypotheses are tested based on distortion parameters complexity (total of two tangential coefficients and one radial coefficient): • Without radial and tangential distortion. • Without tangential distortion but with radial distortion. • With both radial and tangential distortion.

  3. M. T. El-Melegy and A. A. Farag, “Nonmetric lens distortion calibration: closed-form solutions, robust estimation and model selection,” in Ninth IEEE Int. Conf. on Computer Vision, 2003. vol. 1, pp. 554-559, 13-16 Oct. 2003. • Geometric inference. • Criterion defined in terms of the fitness of the data to the model and the complexity of the model. • Complexity of the model is dependent on the number of lines used for distortion calibration and the number of points used. • Three models are tested with AIC and MDL on synthetic data: • Without distortion. • One radial distortion coefficient. • Two radial distortion coefficients.

  4. M, Ahmed and A. Farag, “Nonmetric Calibration of Camera Lens Distortion: Differential Methods and Robust Estimation,” in IEEE Transactions on Image Processing, vol. 14, Iss. 8, pp. 1215-1230, August 2005. • In the conclusion the authors plans are to incorporate statistical model selection.

  5. [Broaddus05] C. Broaddus, “Universal Geometric Camera Calibration with Statistical Model Selection,” Masters Thesis, Department of Electrical Engineering, The University of Tennessee, Knoxville, TN 2005. • Show results on real wide angle data and not just synthetic data. • Implement AIC for five model selection criterions (AIC MDL BIC SSD CAIC) others show it for only AIC and MDL. • AIC model is penalized only for the number of distortion coefficients. AIC model is not penalized for features found in the image (number of images and number of points).

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