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A NON PARAMETRIC METHOD FOR VIDEO CAMERA CALIBRATION USING A NEURAL NETWORK

An efficient technique for video camera calibration is presented. Unlike the methods reported up to now, it does not require parameter estimation (lense distortion coefficients, focal distance, rotation and translation matrices, etc.). The method consists essentially of a mapping from the camera space onto that of real positions by means of a neural network (two-layer perceptron) trained with an original algorithm for neural network construction. This is an approximate technique, i.e. precision increases with the sample size and can be as large as needed by growing that size and the computing time. We show that it is possible to obtain good approximations with low computational costs (processor and memory).