Bansal, M., Jain, A., Camus, T., & Das, A., (June 2005). “Towards a Practical Stereo Vision Sensor,” Computer Vision and Pattern Recognition – Workshops, 2005. CVPR Workshops. IEEE Computer Society Conference on, vol., no., pp.63,63, 25-25.
Development of a practical stereo vision sensor for real-world applications must account for the variability of high-volume production processes and the impact of unknown environmental conditions during its operation. One critical factor of stereo depth estimation performance is the relative alignment of the stereo camera pair. While imperfectly aligned stereo cameras may be rectified in the image domain, there are some errors introduced by both the calibration recovery and image rectification processes. Finally, additional uncalibrated misalignments, for example due to thermal or mechanical deformation in a harsh automotive environment, may occur which will further deteriorate stereo depth estimation. This paper describes an experimental framework for determining these limits using image processing algorithms, operating on graphically synthesized imagery, with performance envelope validation on real stereo image data.