A 3D Imaging Framework Based on High-Resolution Photometric-Stereo and Low-Resolution Depth |
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Authors: | Zheng Lu Yu-Wing Tai Fanbo Deng Moshe Ben-Ezra Michael S Brown |
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Affiliation: | 1. National University of Singapore, Computing 1, 13 Computing Drive, Singapore, 127110, Singapore 3. Microsoft Research Asia, Building 2, No. 5 Dan Ling Street, Haidian District, Beijing, 10080, People’s Republic of China 2. Department of Computer Science, Korea Advanced Institute of Science and Technology, Guseong-dong, Yuseong-gu, Daejeon, 305-701, South Korea
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Abstract: | This paper introduces a 3D imaging framework that combines high-resolution photometric stereo and low-resolution depth. Our approach targets imaging scenarios based on either macro-lens photography combined with focal stacking or a large-format camera that are able to image objects with more than 600 samples per mm $^2$ . These imaging techniques allow photometric stereo algorithms to obtain surface normals at resolutions that far surpass corresponding depth values obtained with traditional approaches such as structured-light, passive stereo, or depth-from-focus. Our work offers two contributions for 3D imaging based on these scenarios. The first is a multi-resolution, patched-based surface reconstruction scheme that can robustly handle the significant resolution difference between our surface normals and depth samples. The second is a method to improve the initial normal estimation by using all the available focal information for images obtained using a focal stacking technique. |
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