International Journal of Computer Vision

, Volume 102, Issue 1, pp 18-32

First online:

A 3D Imaging Framework Based on High-Resolution Photometric-Stereo and Low-Resolution Depth

  • Zheng LuAffiliated withNational University of SingaporeMicrosoft Research Asia Email author 
  • , Yu-Wing TaiAffiliated withDepartment of Computer Science, Korea Advanced Institute of Science and Technology
  • , Fanbo DengAffiliated withNational University of Singapore
  • , Moshe Ben-EzraAffiliated withMicrosoft Research Asia
  • , Michael S. BrownAffiliated withNational University of Singapore

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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.


3D Reconstruction High resolution Photometric stereo Focal stack