Digital inspection: an interactive stage for viewing surface details
Proceedings of the 2008 symposium on Interactive 3D graphics and games
Color Subspaces as Photometric Invariants
International Journal of Computer Vision
Stereo Image Analysis of Non-Lambertian Surfaces
International Journal of Computer Vision
Dynamic shape capture using multi-view photometric stereo
ACM SIGGRAPH Asia 2009 papers
Median Photometric Stereo as Applied to the Segonko Tumulus and Museum Objects
International Journal of Computer Vision
Multi-view reconstruction under varying illumination conditions
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Temporal upsampling of performance geometry using photometric alignment
ACM Transactions on Graphics (TOG)
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
DECHO—a framework for the digital exploration of cultural heritage objects
Journal on Computing and Cultural Heritage (JOCCH)
Structure from motion and photometric stereo for dense 3D shape recovery
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing: Part I
Dense photometric stereo by expectation maximization
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Translational photometric alignment of single-view image sequences
Computer Vision and Image Understanding
3D reconstruction in laparoscopy with close-range photometric stereo
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Evaluating the effect of diffuse light on photometric stereo reconstruction
Machine Vision and Applications
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We introduce an iterative algorithm for shape reconstruction from multiple images of a moving (Lambertian) object illuminated by distant (and possibly time varying) lighting. Starting with an initial piecewise linear surface, the algorithm iteratively estimates a new surface based on the previous surface estimate and the photometric information available from the input image sequence. During each iteration, standard photometric stereo techniques are applied to estimate the surface normals up to an unknown generalized bas-relief transform, and a new surface is computed by integrating the estimated normals. The algorithm essentially consists of a sequence of matrix factorizations (of intensity values) followed by minimization using gradient descent (integration of the normals). Conceptually, the algorithm admits a clear geometric interpretation, which is used to provide a qualitative analysis of the algorithm驴s convergence. Implementation-wise, it is straightforward, being based on several established photometric stereo and structure from motion algorithms. We demonstrate experimentally the effectiveness of our algorithm using several videos of hand-held objects moving in front of a fixed light and camera.