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在空间变化照明下光传输的频率-空间的分解和获取

Frequency-Space Decomposition and Acquisition of Light Transport under Spatially Varying Illumination
课程网址: http://videolectures.net/eccv2012_ramamoorthi_decomposition/  
主讲教师: Bernt Schiele; David Forsyth; Ravi Ramamoorthi
开课单位: 加州大学伯克利分校
开课时间: 2012-11-12
课程语种: 英语
中文简介:
我们表明,在空间变化的光照下,漫反射场景的光传输可以分解为直接、近距离(次表面散射和局部反射)和远距离传输(漫反射)。我们表明,这三个组件的传输在空间或频率域都是冗余的,并且可以使用适当的照明模式进行分离。我们提出了一种新的、有效的方法来顺序分离和获取组件传输。首先,我们通过将泛光图像的直接全局分离技术扩展到全传输矩阵来获得直接传输。接下来,我们通过频域内均匀采样的照明模式分离并获取近距离传输。最后,我们通过照明低频模式来获得远距离传输。从理论上讲,我们的获取方法实现了模型在所需模式数量上的下限。我们通过使用蛮力方法来量化模式数量上的节省。我们通过实例验证了我们的观察和获取方法。
课程简介: We show that, under spatially varying illumination, the light transport of diffuse scenes can be decomposed into direct, near-range (subsurface scattering and local inter-reflections) and far-range transports (diffuse inter-reflections). We show that these three component transports are redundant either in the spatial or the frequency domain and can be separated using appropriate illumination patterns. We propose a novel, efficient method to sequentially separate and acquire the component transports. First, we acquire the direct transport by extending the direct-global separation technique from floodlit images to full transport matrices. Next, we separate and acquire the near-range transport by illuminating patterns sampled uniformly in the frequency domain. Finally, we acquire the far-range transport by illuminating low-frequency patterns. We show that theoretically, our acquisition method achieves the lower bound our model places on the required number of patterns. We quantify the savings in number of patterns over the brute force approach. We validate our observations and acquisition method with rendered and real examples throughout.
关 键 词: 计算机视觉; 间漫反射; 光照模式分离
课程来源: 视频讲座网
最后编审: 2021-01-28:nkq
阅读次数: 26