Dense, accurate optical flow estimation with piecewise parametric model
Dense, accurate optical flow estimation with piecewise parametric model
复制标题
DOI：
10.1109/cvpr.2015.7298704
复制
发表时间：
2015-06
期刊：
影响因子：
--
通讯作者：
Jiaolong Yang;Hongdong Li
中科院分区：
文献类型：
--
作者：
Jiaolong Yang;Hongdong Li
本文提出了一种计算稠密、精确光流场的简单方法。它复兴了分段参数流模型的早期思想。一个关键的创新是，我们将流场分段拟合到各种参数模型，其中每一段的域（即，每个部件的形状、位置和尺寸）被自适应地确定，同时保持全局部件间流动连续性约束。我们通过能量最小化的多模型拟合方案来实现这一点。我们的能量同时考虑了分段常数模型假设和流场连续性约束，使所提出的方法能够有效地处理均匀运动和复杂运动。三个公共光流基准（KITTI，MPI Sintel和Middlebury）的实验表明，我们的方法相比，最先进的优越性：它实现了顶级性能的所有三个基准。
This paper proposes a simple method for estimating dense and accurate optical flow field. It revitalizes an early idea of piecewise parametric flow model. A key innovation is that, we fit a flow field piecewise to a variety of parametric models, where the domain of each piece (i.e., each piece's shape, position and size) is determined adaptively, while at the same time maintaining a global inter-piece flow continuity constraint. We achieve this by a multi-model fitting scheme via energy minimization. Our energy takes into account both the piecewise constant model assumption and the flow field continuity constraint, enabling the proposed method to effectively handle both homogeneous motions and complex motions. The experiments on three public optical flow benchmarks (KITTI, MPI Sintel, and Middlebury) show the superiority of our method compared with the state of the art: it achieves top-tier performances on all the three benchmarks.