2026-02-17 コロンビア大学
An artist’s rendering of micro phase shifting. Photo Credit:Anna Collevecchio/Columbia Engineering
＜関連情報＞
- https://www.engineering.columbia.edu/about/news/columbias-3d-vision-technology-powers-factory-automation
- https://ieeexplore.ieee.org/document/6247753
- https://dl.acm.org/doi/10.1145/1141911.1141977
マイクロ位相シフト Micro Phase Shifting
Mohit Gupta; Shree K. Nayar
2012 IEEE Conference on Computer Vision and Pattern Recognition Date Added to IEEE Xplore: 26 July 2012
DOI:https://doi.org/10.1109/CVPR.2012.6247753
Abstract
We consider the problem of shape recovery for real world scenes, where a variety of global illumination (inter-reflections, subsurface scattering, etc.) and illumination defocus effects are present. These effects introduce systematic and often significant errors in the recovered shape. We introduce a structured light technique called Micro Phase Shifting, which overcomes these problems. The key idea is to project sinusoidal patterns with frequencies limited to a narrow, high-frequency band. These patterns produce a set of images over which global illumination and defocus effects remain constant for each point in the scene. This enables high quality reconstructions of scenes which have traditionally been considered hard, using only a small number of images. We also derive theoretical lower bounds on the number of input images needed for phase shifting and show that Micro PS achieves the bound.
高周波照明を用いたシーンの直接成分と全体成分の高速分離 Fast separation of direct and global components of a scene using high frequency illumination
Shree K. Nayar,Gurunandan Krishnan,Michael D. Grossberg,Ramesh Raskar
ACM Transactions on Graphics Published: 01 July 2006
DOI:https://doi.org/10.1145/1141911.1141977
Abstract
We present fast methods for separating the direct and global illumination components of a scene measured by a camera and illuminated by a light source. In theory, the separation can be done with just two images taken with a high frequency binary illumination pattern and its complement. In practice, a larger number of images are used to overcome the optical and resolution limitations of the camera and the source. The approach does not require the material properties of objects and media in the scene to be known. However, we require that the illumination frequency is high enough to adequately sample the global components received by scene points. We present separation results for scenes that include complex interreflections, subsurface scattering and volumetric scattering. Several variants of the separation approach are also described. When a sinusoidal illumination pattern is used with different phase shifts, the separation can be done using just three images. When the computed images are of lower resolution than the source and the camera, smoothness constraints are used to perform the separation using a single image. Finally, in the case of a static scene that is lit by a simple point source, such as the sun, a moving occluder and a video camera can be used to do the separation. We also show several simple examples of how novel images of a scene can be computed from the separation results.
