论文标题
使用图像特征和像素强度进行统一的同型估算方法
Towards a Unified Approach to Homography Estimation Using Image Features and Pixel Intensities
论文作者
论文摘要
同型矩阵是各种基于视觉的机器人任务中的关键组成部分。传统上，同构估计算法分为基于特征或强度。后者的主要优点是它们的多功能性，准确性和鲁棒性变化。另一方面，与基于特征的解决方案相比，它们具有较小的收敛域。因此，它们的组合是有希望的，但是现有技术仅依次应用它们。本文提出了一种新的混合方法，将这两个类别统一为单个非线性优化过程，应用相同的最小化方法，并使用相同的同型参数化和翘曲功能。使用经典测试框架的实验验证表明，与每个类别相比，所提出的统一方法提高了收敛性。这些也可以在视觉跟踪应用程序中证明。作为最终的贡献，我们对算法的现成实施是向研究界公开使用的。
The homography matrix is a key component in various vision-based robotic tasks. Traditionally, homography estimation algorithms are classified into feature- or intensity-based. The main advantages of the latter are their versatility, accuracy, and robustness to arbitrary illumination changes. On the other hand, they have a smaller domain of convergence than the feature-based solutions. Their combination is hence promising, but existing techniques only apply them sequentially. This paper proposes a new hybrid method that unifies both classes into a single nonlinear optimization procedure, applies the same minimization method, and uses the same homography parametrization and warping function. Experimental validation using a classical testing framework shows that the proposed unified approach has improved convergence properties compared to each individual class. These are also demonstrated in a visual tracking application. As a final contribution, our ready-to-use implementation of the algorithm is made publicly available to the research community.
