Optic Flow Goes Stereo: A Variational Method for Estimating Discontinuity-Preserving Dense Disparity Maps
Optic Flow Goes Stereo: A Variational Method for Estimating Discontinuity-Preserving Dense Disparity Maps
复制标题
DOI：
10.1007/11550518_5
复制
发表时间：
2005-08
期刊：
影响因子：
--
通讯作者：
Natalia Slesareva;Andrés Bruhn;J. Weickert
中科院分区：
文献类型：
--
作者：
Natalia Slesareva;Andrés Bruhn;J. Weickert
我们提出了一种新的变分方法估计稠密视差图的立体图像。它将对极线约束集成到目前最精确的光流法中（Broxet al.2004）。通过这种方式，获得了一种新的方法，与现有的变分方法相比，该方法具有以下几个优点：（i）由于使用全变分作为解驱动的正则化器，它可以很好地消除不连续性。(ii)它在噪声下表现良好，因为它使用了一个强大的函数来惩罚数据约束的偏差。(iii)通过由粗到细的策略使其最小化在理论上是合理的。仿真和真实数据的实验表明，该方法具有良好的性能和噪声鲁棒性。
We present a novel variational method for estimating dense disparity maps from stereo images. It integrates the epipolar constraint into the currently most accurate optic flow method (Broxet al.2004). In this way, a new approach is obtained that offers several advantages compared to existing variational methods: (i) It preservers discontinuities very well due to the use of the total variation as solution-driven regulariser. (ii) It performs favourably under noise since it uses a robust function to penalise deviations from the data constraints. (iii) Its minimisation via a coarse-to-fine strategy can be theoretically justified. Experiments with both synthetic and real-world data show the excellent performance and the noise robustness of our approach.