Computing Optical Flow with Physical Models of Brightness Variation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Relaxing the Brightness Constancy Assumption in Computing Optical Flow
Relaxing the Brightness Constancy Assumption in Computing Optical Flow
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
IEEE Transactions on Pattern Analysis and Machine Intelligence
Articulated mesh animation from multi-view silhouettes
ACM SIGGRAPH 2008 papers
Performance capture from sparse multi-view video
ACM SIGGRAPH 2008 papers
ACM SIGGRAPH 2008 papers
From obscurances to ambient occlusion: A survey
The Visual Computer: International Journal of Computer Graphics
An Improved Algorithm for TV-L1 Optical Flow
Statistical and Geometrical Approaches to Visual Motion Analysis
Dynamic shape capture using multi-view photometric stereo
ACM SIGGRAPH Asia 2009 papers
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
High-quality single-shot capture of facial geometry
ACM SIGGRAPH 2010 papers
High resolution passive facial performance capture
ACM SIGGRAPH 2010 papers
Illumination-robust variational optical flow using cross-correlation
Computer Vision and Image Understanding
A Database and Evaluation Methodology for Optical Flow
International Journal of Computer Vision
High-quality passive facial performance capture using anchor frames
ACM SIGGRAPH 2011 papers
International Journal of Computer Vision
Fusing Multiview and Photometric Stereo for 3D Reconstruction under Uncalibrated Illumination
IEEE Transactions on Visualization and Computer Graphics
Shading-based dynamic shape refinement from multi-view video under general illumination
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
On-set performance capture of multiple actors with a stereo camera
ACM Transactions on Graphics (TOG)
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We present a general technique for improving space-time reconstructions of deforming surfaces, which are captured in an video-based reconstruction scenario under uniform illumination. Our approach simultaneously improves both the acquired shape as well as the tracked motion of the deforming surface. The method is based on factoring out surface shading, computed by a fast approximation to global illumination called ambient occlusion. This allows us to improve the performance of optical flow tracking that mainly relies on constancy of image features, such as intensity. While cancelling the local shading, we also optimize the surface shape to minimize the residual between the ambient occlusion of the 3D geometry and that of the image, yielding more accurate surface details in the reconstruction. Our enhancement is independent of the actual space-time reconstruction algorithm. We experimentally measure the quantitative improvements produced by our algorithm using a synthetic example of deforming skin, where ground truth shape and motion is available. We further demonstrate our enhancement on a real-world sequence of human face reconstruction.