Perspective reconstruction of non-rigid surfaces from single-view videos

M. Sepehrinour, S. Kasaei
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引用次数: 1

Abstract

A novel algorithm to reconstruct the three-dimensional (3D) structure of non-rigid shapes based on a single view video, considering the perspective projection camera model, is presented in this paper. Even though perspective projection is considered to be the most realistic model and is ideal for a wide range of cameras in machine vision applications, but because of its complex and often non-linear equations, mostly, is approximated by some simpler camera projection models such as orthographic projection, weak perspective projection and so forth. Orthographic reconstruction of non-rigid surfaces has been done by singular value decomposition algorithm and using the orthogonal characteristics of the rotation matrix, but using this simple method, for perspective projection camera model in reconstructing non-rigid surfaces, due to the high complexity and the large number of unknowns, seems impossible. On the other hand since the orthographic projection camera model can be applied only in cases where the 3D scene is in the far distance from the camera (or in the other word, where the depth of the object is assumed to be small compared to the distance of the object to the camera), the need to apply the perspective projection camera model will arises. In this paper we have proposed a novel algorithm for perspective projection reconstruction of non-rigid surfaces from single view videos and overcome all of the complexities and all non-linearity of the perspective projection equations, for the first time. Due to the high number of unknowns, the problem has been divided into two parts of projective depth coefficients extraction and 3D shape reconstruction. The proposed method is evaluated on popular video segmentation datasets and its performance is compared to other available methods. The experiments show that the obtained results of the proposed method were acceptable when compared to the results of the previous methods, while it resolves the failures of those approaches.
单视图视频中非刚性表面的透视重建
提出了一种基于单视图视频的非刚性形状三维结构重建算法,该算法考虑了透视投影摄像机模型。尽管透视投影被认为是最逼真的模型,是机器视觉中广泛应用的理想相机模型,但由于其复杂且往往是非线性的方程,大多数情况下,是由一些更简单的相机投影模型近似,如正射影投影,弱透视投影等。非刚性曲面的正交重建已经通过奇异值分解算法和利用旋转矩阵的正交特性来完成,但是使用这种简单的方法,对于透视投影相机模型在重建非刚性曲面时,由于复杂度高和未知量大,似乎是不可能的。另一方面,由于正投影相机模型只能应用于3D场景距离相机较远的情况下(或者换句话说,假设物体的深度与物体到相机的距离相比较小),因此需要应用透视投影相机模型。本文首次提出了一种基于单视图视频的非刚性曲面透视投影重建算法,克服了透视投影方程的所有复杂性和非线性。由于未知量较多,将问题分为投影深度系数提取和三维形状重建两部分。在流行的视频分割数据集上对该方法进行了评估,并与其他可用方法进行了性能比较。实验结果表明,该方法得到的结果与以往方法的结果相比是可以接受的,同时也解决了以往方法的不足。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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