自我运动和全方位相机

J. Gluckman, S. Nayar
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引用次数: 259

摘要

最近对图像传感器的研究已经生产出具有非常大视场的相机。计算机视觉研究的一个领域将受益于这项技术,即从一系列图像中计算相机运动(自我运动)。传统摄像机由于平移方向可能在视场之外,使得摄像机运动计算对噪声比较敏感。在本文中,我们提出了一种利用全向相机恢复自我运动的方法。考虑到球面投影与广角成像设备之间的关系,我们提出利用相机投影模型与球面投影之间变换的雅可比矩阵,将图像速度向量映射到球面上。一旦速度矢量被映射到一个球体,我们展示了如何现有的自我运动算法可以应用,并提出了一些实验结果。这些结果证明了用全向相机计算自我运动的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ego-motion and omnidirectional cameras
Recent research in image sensors has produced cameras with very large fields of view. An area of computer vision research which will benefit from this technology is the computation of camera motion (ego-motion) from a sequence of images. Traditional cameras stiffer from the problem that the direction of translation may lie outside of the field of view, making the computation of camera motion sensitive to noise. In this paper, we present a method for the recovery of ego-motion using omnidirectional cameras. Noting the relationship between spherical projection and wide-angle imaging devices, we propose mapping the image velocity vectors to a sphere, using the Jacobian of the transformation between the projection model of the camera and spherical projection. Once the velocity vectors are mapped to a sphere, we show how existing ego-motion algorithms can be applied and present some experimental results. These results demonstrate the ability to compute ego-motion with omnidirectional cameras.
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