多个宽基线视图的密集匹配

C. Strecha, T. Tuytelaars, L. Gool
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引用次数: 197

摘要

本文描述了一种基于偏微分方程的多幅宽基线图像密集深度提取方法。重点在于只使用少量的图像。这些多个宽基线视图的集成是由系统在匹配不同视图方面的相对置信度指导的。这种加权是细粒度的,因为它是在每次迭代中为每个像素确定的。在视图内的空间通信和视图之间的信息交换方面,可靠的信息以不可靠的数据为代价迅速传播。图像之间的强度变化可以用类似的细粒度方式处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dense matching of multiple wide-baseline views
This paper describes a PDE-based method for dense depth extraction from multiple wide-baseline images. Emphasis lies on the usage of only a small amount of images. The integration of these multiple wide-baseline views is guided by the relative confidence that the system has in the matching to different views. This weighting is fine-grained in that it is determined for every pixel at every iteration. Reliable information spreads fast at the expense of less reliable data, both in terms of spatial communications within a view and in terms of information exchange between the views. Changes in intensity between images can be handled in a similar fine grained fashion.
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