Image-based spatio-temporal modeling and view interpolation of dynamic events
ACM Transactions on Graphics (TOG)
Performance relighting and reflectance transformation with time-multiplexed illumination
ACM SIGGRAPH 2005 Papers
Shapelets Correlated with Surface Normals Produce Surfaces
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
On the Removal of Shadows from Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Particle Video: Long-Range Motion Estimation using Point Trajectories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Surface Capture for Performance-Based Animation
IEEE Computer Graphics and Applications
Articulated mesh animation from multi-view silhouettes
ACM SIGGRAPH 2008 papers
Dynamic shape capture using multi-view photometric stereo
ACM SIGGRAPH Asia 2009 papers
Dynamic photometric stereo-a new technique for moving surface analysis
Image and Vision Computing
Dense and accurate spatio-temporal multi-view stereovision
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Rapid acquisition of specular and diffuse normal maps from polarized spherical gradient illumination
EGSR'07 Proceedings of the 18th Eurographics conference on Rendering Techniques
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In this paper we present a novel method to apply photometric stereo on textured dynamic surfaces. We aim at exploiting the high accuracy of photometric stereo and reconstruct local surface orientation from illumination changes. The main difficulty derives from the fact that photometric stereo requires varying illumination while the object remains still, which makes it quite impractical to use for dynamic surfaces. Using coloured lights gives a clear solution to this problem; however, the system of equations is still ill-posed and it is ambiguous whether the change of an observed surface colour is due to the change of the surface gradient or of the surface reflectance. In order to separate surface orientation from reflectance, our method tracks texture changes over time and exploits surface reflectance's temporal constancy. This additional constraint allows us to reformulate the problem as an energy functional minimisation, solved by a standard quasi-Newton method. Our method is tested both on real and synthetic data, quantitatively evaluated and compared to a state-of-the-art method.