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A Linear Method to Derive 3D Projective Invariants from 4 Uncalibrated Images

机译:从4个未校准图像中导出3D投影不变的线性方法

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A well-known method proposed by Quan to compute projective invariants of 3D points uses six points in three 2D images. The method is nonlinear and complicated. It usually produces three possible solutions. It is noted previously that the problem can be solved directly and linearly using six points in five images. This paper presents a method to compute projective invariants of 3D points from four uncalibrated images directly. For a set of six 3D points in general position, we choose four of them as the reference basis and represent the other two points under this basis. It is known that the cross ratios of the coefficients of these representations are projective invariant. After a series of linear transformations, a system of four bilinear equations in the three unknown projective invariants is derived. Systems of nonlinear multivariable equations are usually hard to solve. We show that this form of equations can be solved linearly and uniquely. This finding is remarkable. It means that the natural configuration of the projective reconstruction problem might be six points and four images. The solutions are given in explicit formulas.
机译:Quan提出的众所周知的方法来计算3D点的投影不变性使用三个2D图像中的六个点。该方法是非线性和复杂的。它通常产生三种可能的解决方案。先前,先前,问题可以使用五个图像中的六个点直接和线性地解决问题。本文介绍了一种方法,可以直接从四个未校准图像计算3D点的投影不变。对于一系列常规位置的一组六个3D点,我们选择其中四个作为参考基础,并在此基础下代表另外两点。众所周知,这些表示的系数的交叉比是投影不变的。在一系列线性变换之后,推导出三个未知的投影不变性中的四个双线性方程系统。非线性多变量方程的系统通常很难解决。我们表明,这种形式的等式可以线性和唯一地解决。这一发现是显着的。这意味着投影重建问题的自然配置可能是六点和四个图像。解决方案以明确的公式给出。

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