极化(电化学)
方位角
计算机科学
模棱两可
光学
计算机视觉
人工智能
物理
化学
物理化学
程序设计语言
作者
Achuta Kadambi,Vage Taamazyan,Boxin Shi,Ramesh Raskar
标识
DOI:10.1109/iccv.2015.385
摘要
Coarse depth maps can be enhanced by using the shape information from polarization cues. We propose a framework to combine surface normals from polarization (hereafter polarization normals) with an aligned depth map. Polarization normals have not been used for depth enhancement before. This is because polarization normals suffer from physics-based artifacts, such as azimuthal ambiguity, refractive distortion and fronto-parallel signal degradation. We propose a framework to overcome these key challenges, allowing the benefits of polarization to be used to enhance depth maps. Our results demonstrate improvement with respect to state-of-the-art 3D reconstruction techniques.
科研通智能强力驱动
Strongly Powered by AbleSci AI