Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109.
IEEE Trans Pattern Anal Mach Intell. 1987 Mar;9(3):356-69. doi: 10.1109/tpami.1987.4767919.
Stereo information can be obtained using a moving camera. If a dynamic scene is acquired using a translating camera and the camera motion parameters are known, then the analysis of the scene may be facilitated by ego-motion complex logarithmic mapping (ECLM). It is shown in this paper that by using the complex logarithmic mapping (CLM) with respect to the focus of expansion, the depth of stationary components can be determined easily in the transformed image sequence. The proposed approach for depth recovery avoids the difficult problems of establishing correspondence and computation of optical flow, by using the ego-motion information. An added advantage of the CLM will be the invariances it offers. We report our experiments with synthetic data to show the sensitivity of the depth recovery, and show results of real scenes to demonstrate the efficacy of the proposed motion stereo in applications such as autonomous navigation.
可以使用移动摄像机获取立体信息。如果使用平移摄像机获取动态场景，并且知道摄像机运动参数，则通过自运动复对数映射（ECLM）可以方便地分析场景。本文表明，通过使用关于扩展焦点的复对数映射（CLM），可以在变换后的图像序列中轻松确定静止分量的深度。所提出的深度恢复方法通过使用自运动信息避免了建立对应关系和计算光流的难题。CLM 的一个附加优点是它提供的不变性。我们报告了使用合成数据的实验结果，以显示深度恢复的敏感性，并展示真实场景的结果，以证明所提出的运动立体在自主导航等应用中的有效性。
