We report on experiments with a mobile robot using one vision process (forward motion vision) to calibrate another (stereo vision) without resorting to any external units of measurement. Both are calibrated to a velocity dependent coordinate system which is natural to the task of obstacle avoidance. The foundations of these algorithms, in a world of perfect measurement, are quite elementary. The contribution of this work is to make them noise tolerant while remaining simple computationally. Both the algorithms and the calibration procedure are easy to implement and have shallow computational depth, making them (1) run at reasonable speed on moderate uni-processors, (2) appear practical to run continuously, maintaining an up-to-the-second calibration on a mobile robot, and (3) appear to be good candidates for massively parallel implementations.