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Backpropagation neural network for stereoscopic vision calibration

Calibration is the process of establishing the relationship between camera and global coordinate systems. In the case of stereoscopic vision, the relationship between two cameras and a global coordinate system must be established. Many techniques have been proposed to perform the calibration process most requiring a substantial amount of programming and special test fixtures. This paper proposes a backpropagation neural network to estimate the transformation between two camera systems and a global coordinate system. The approach requires minimum programming and no special test fixtures. This paper describes the artificial neural network architecture along with the procedures used in training. Encouraging results are obtained from preliminary test runs