Geiger D, Yuille A
Massachusetts Institute of Technology, Artificial Intelligence Laboratory, Cambridge, MA 02139.
Biol Cybern. 1989;62(2):117-28. doi: 10.1007/BF00203000.
We describe a method to solve stereo correspondence using controlled eye (or camera) movements. Eye movements supply additional image frames and monocular depth estimate, which can be used to constrain stereo matching. Because the eye movements are small, traditional stereo techniques of stereo with multiple frame will not work. We develop an alternative approach using a systematic analysis to define a probability distribution for the errors. Our matching strategy then matches the most probable points first, thereby reducing the ambiguity for the remaining matches. We demonstrate this algorithms with several examples.
我们描述了一种使用可控眼球(或相机)运动来解决立体匹配问题的方法。眼球运动提供了额外的图像帧和单目深度估计,可用于约束立体匹配。由于眼球运动幅度较小,传统的多帧立体技术将无法适用。我们开发了一种替代方法,通过系统分析来定义误差的概率分布。然后,我们的匹配策略首先匹配最有可能的点,从而减少其余匹配的模糊性。我们用几个例子演示了这种算法。