Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo

Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo

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Multi-spectral photometric stereo can recover pixel-wise surface normal from a single RGB image.The difficulty lies in that the intensity in each channel Fan Shop - NCAA - Clothing is the tangle of illumination, albedo and camera response; thus, an initial estimate of the normal is required in optimization-based solutions.In this paper, we propose to make a rough depth estimation using the deep convolutional neural network (CNN) instead of using depth sensors or binocular stereo devices.Since high-resolution ground-truth data is expensive Speaker Accessories to obtain, we designed a network and trained it with rendered images of synthetic 3D objects.

We use the model to predict initial normal of real-world objects and iteratively optimize the fine-scale geometry in the multi-spectral photometric stereo framework.The experimental results illustrate the improvement of the proposed method compared with existing methods.