文件名称:Gupta_CVPR12
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- 图形图像处理(光照,映射..)
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- 2012-12-06
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CVPR2012_oral
Micro Phase Shifting-We consider the problem of shape recovery for real
world scenes, where a variety of global illumination (in-
terreflections, subsurface scattering, etc.) and illumi-
nation defocus effects are present. These effects in-
troduce systematic and often significant errors in the
recovered shape. We introduce a structured light tech-
nique 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 im-
ages over which global illumination and defocus effects
remain constant for each point in the scene. This en-
ables 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.
Micro Phase Shifting-We consider the problem of shape recovery for real
world scenes, where a variety of global illumination (in-
terreflections, subsurface scattering, etc.) and illumi-
nation defocus effects are present. These effects in-
troduce systematic and often significant errors in the
recovered shape. We introduce a structured light tech-
nique 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 im-
ages over which global illumination and defocus effects
remain constant for each point in the scene. This en-
ables 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.
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