NRSfM使用局部刚性

A. Rehan, Aamer Zaheer, Ijaz Akhter, Arfah Saeed, M. Usmani, Bilal Mahmood, Sohaib Khan
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引用次数: 18

摘要

本文证明了典型的非刚性结构在时间和空间上往往可以很好地近似为局部刚性子结构。具体来说,我们假设:1)结构在短的局部时间窗内可以近似为刚性;2)一些点对在空间上保持相对刚性,在序列中它们之间保持固定距离。首先,我们在滑动时间窗口上使用刚性SfM中的三角化约束来获得非刚性3D结构的初始估计。然后,我们自动识别出该结构中相对刚性的点对,并同时使用它们的长度常数与三角化约束来改进结构估计。局部分解固有地处理小摄像机运动、短序列和显著的自然遮挡,比非刚性分解方法表现得更好。我们展示了更稳定和准确的结果,相比于最先进的,甚至从15帧开始的短序列,包含相机旋转小至2°和高达50%的连续缺失数据。
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NRSfM using local rigidity
In this paper we show that typical nonrigid structure can often be approximated well as locally rigid sub-structures in time and space. Specifically, we assume that: 1) the structure can be approximated as rigid in a short local time window and 2) some point- pairs stay relatively rigid in space, maintaining a fixed distance between them during the sequence. First, we use the triangulation constraints in rigid SfM over a sliding time window to get an initial estimate of the nonrigid 3D structure. Then we automatically identify relatively rigid point-pairs in this structure, and use their length-constancy simultaneously with triangulation constraints to refine the structure estimate. Local factorization inherently handles small camera motion, short sequences and significant natural occlusions gracefully, performing better than nonrigid factorization methods. We show more stable and accurate results as compared to the state-of-the art on even short sequences starting from 15 frames only, containing camera rotations as small as 2° and up to 50% contiguous missing data.
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