Determining a depth map using a dual photometric stereo
International Journal of Robotics Research
The Computation of Visible-Surface Representations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape from shading
Separation of Reflection Components Using Color and Polarization
International Journal of Computer Vision
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using 3-Dimensional Meshes To Combine Image-Based and Geometry-Based Constraints
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
Interactive digital photomontage
ACM SIGGRAPH 2004 Papers
Efficiently combining positions and normals for precise 3D geometry
ACM SIGGRAPH 2005 Papers
A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Visible Surface Reconstruction from Normals with Discontinuity Consideration
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
IEEE Transactions on Pattern Analysis and Machine Intelligence
Interactive normal reconstruction from a single image
ACM SIGGRAPH Asia 2008 papers
An out-of-core sparse Cholesky solver
ACM Transactions on Mathematical Software (TOMS)
Invertible motion blur in video
ACM SIGGRAPH 2009 papers
Dynamic shape capture using multi-view photometric stereo
ACM SIGGRAPH Asia 2009 papers
3D Computer Vision: Efficient Methods and Applications
3D Computer Vision: Efficient Methods and Applications
Advances in the cooperation of shape from shading and stereo vision
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
High-accuracy stereo depth maps using structured light
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
What is the range of surface reconstructions from a gradient field?
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Building a digital model of Michelangelo's Florentine Pieta
IEEE Computer Graphics and Applications
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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.