Automated parameter tuning in stereo vision under time constraints

A method for tuning parameters under a fixed time constraint for a general binocular stereo-vision algorithm is presented. TEACHER 4.2, a generate-and-test system that systematically generates new parameter values by analyzing the results of previous tests and performs limited and controlled tests on the candidates generated using high-speed computers, is discussed. The system is modeled as a statistical selection problem operating under a given time constraint. Results show that the system can find new parameter-value sets which in some cases are better than the ones originally found by extensive hand-tuning and commonly used heuristics, and that different parameter values may be required under different objectives and performance constraints