Multi-view Photometric Stereo with Spatially Varying Isotropic Materials



We present a method to capture both 3D shape and spatially varying reflectance with a multi-view photometric stereo technique that works for general isotropic materials. Our data capture setup is simple, which consists of only a digital camera and a handheld light source. From a single viewpoint, we use a set of photometric stereo images to identify surface points with the same distance to the camera. We collect this information from multiple viewpoints and combine it with structure-from-motion to obtain a precise reconstruction of the complete 3D shape. The spatially varying isotropic bidirectional reflectance distribution function (BRDF) is captured by simultaneously inferring a set of basis BRDFs and their mixing weights at each surface point. According to our experiments, the captured shapes are accurate to 0.3 millimeters. The captured reflectance has relative root-mean-square error (RMSE) of 9% (re-rendered images differ from real photographs by about 6 gray levels).

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"Multi-view Photometric Stereo with Spatially Varying Isotropic Materials", Zhenglong Zhou, Zhe Wu, Ping Tan, IEEE Conference on Computer Vision and Patten Recognition (CVPR), Oregon, USA, Jun. 2013.

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