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Inextensible Non-Rigid Shape-from-Motion by Second-Order Cone Programming

机译:通过二阶锥编程进行不可扩展的非刚性运动定型

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We present a global and convex formulation for template-less 3D reconstruction of a deforming object with the perspective camera. We show for the first time how to construct a Second-Order Cone Programming (SOCP) problem for Non-Rigid Shape-from-Motion (NRSfM) using the Maximum-Depth Heuristic (MDH). In this regard, we deviate strongly from the general trend of using affine cameras and factorization-based methods to solve NRSfM. In MDH, the points' depths are maximized so that the distance between neighbouring points in camera space are upper bounded by the geodesic distance. In NRSfM both geodesic and camera space distances are unknown. We show that, nonetheless, given point correspondences and the camera's intrinsics the whole problem is convex and solvable with SOCP. We show with extensive experiments that our method accurately reconstructs quasi-isometric surfaces from partial views under articulated and strong deformations. It naturally handles missing correspondences, non-smooth objects and is very simple to implement compared to previous methods, with only one free parameter (the neighbourhood size).
机译:我们提出了一种全局和凸形式,用于使用透视相机对变形对象进行无模板3D重建。我们首次展示了如何使用最大深度启发式算法(MDH)构造非刚性运动形状(NRSfM)的二阶锥规划(SOCP)问题。在这方面,我们与使用仿射相机和基于因子分解的方法来解决NRSfM的总体趋势大相径庭。在MDH中,点的深度最大,因此相机空间中相邻点之间的距离以测地距离为上限。在NRSfM中,测地距离和相机空间距离都是未知的。我们表明,尽管如此,给定点对应关系和相机的本征,使用SOCP可以解决整个问题。我们通过广泛的实验表明,我们的方法从关节运动和强力变形下的局部视图中准确地重建了准等距曲面。它自然可以处理丢失的对应关系,非平滑的对象,并且与以前的方法相比,实现起来非常简单,只有一个自由参数(邻居大小)。

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