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Extending shape-from-motion to noncentral onmidirectional cameras

机译:将运动形状扩展到非中央对向摄像机

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Algorithms for shape-from-motion simultaneously estimate the camera motion and scene structure. When extended to omnidirectional cameras, shape-from-motion algorithms are likely to provide robust motion estimates, in particular, because of the camera's wide field of view. In this paper, we describe both batch and online shape-from-motion algorithms for omnidirectional cameras, and a precise calibration technique that improves the accuracy of both methods. The shape-from-motion and calibration methods are general, and they handle a wide variety of omnidirectional camera geometries. In particular, the methods do not require that the camera-mirror combination have a single center of projection. We describe a noncentral camera that we have developed, and show experimentally that combining shape-from-motion with this design produces highly accurate motion estimates.
机译:用于从运动中获取形状的算法会同时估算摄像机的运动和场景结构。当扩展到全向摄像机时,“运动形状”算法很可能会提供可靠的运动估计,尤其是因为摄像机的视野很广。在本文中,我们描述了用于全向相机的批处理和在线运动成型算法,以及一种精确的校准技术,可提高这两种方法的准确性。运动成型和校准方法是通用的,它们可以处理多种全向摄像机几何形状。特别地,该方法不需要照相机-镜子组合具有单个投影中心。我们描述了我们开发的非中央相机,并通过实验证明了将运动形状与该设计结合起来可以产生高度准确的运动估计。

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