Performance-driven facial animation
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3-D Motion Estimation in Model-Based Facial Image Coding
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Cross-parameterization and compatible remeshing of 3D models
ACM SIGGRAPH 2004 Papers
Multi-scale capture of facial geometry and motion
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ACM SIGGRAPH 2009 Courses
Temporal upsampling of performance geometry using photometric alignment
ACM Transactions on Graphics (TOG)
High-quality single-shot capture of facial geometry
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High resolution passive facial performance capture
ACM SIGGRAPH 2010 papers
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EGSR'07 Proceedings of the 18th Eurographics conference on Rendering Techniques
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Lightweight binocular facial performance capture under uncontrolled lighting
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Online modeling for realtime facial animation
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ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
3D shape regression for real-time facial animation
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
Realtime facial animation with on-the-fly correctives
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
An anchor patch based optimization framework for reducing optical flow drift in long image sequences
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
High fidelity facial animation capture and retargeting with contours
Proceedings of the 12th ACM SIGGRAPH/Eurographics Symposium on Computer Animation
High-fidelity facial performance capture with non-sequential temporal alignment
Proceedings of the 3rd Symposium on Facial Analysis and Animation
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ACM Transactions on Graphics (TOG)
Reconstructing detailed dynamic face geometry from monocular video
ACM Transactions on Graphics (TOG)
Augmenting physical avatars using projector-based illumination
ACM Transactions on Graphics (TOG)
Sparse localized deformation components
ACM Transactions on Graphics (TOG)
Animation-aware quadrangulation
SGP '13 Proceedings of the Eleventh Eurographics/ACMSIGGRAPH Symposium on Geometry Processing
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We present a new technique for passive and markerless facial performance capture based on anchor frames. Our method starts with high resolution per-frame geometry acquisition using state-of-the-art stereo reconstruction, and proceeds to establish a single triangle mesh that is propagated through the entire performance. Leveraging the fact that facial performances often contain repetitive subsequences, we identify anchor frames as those which contain similar facial expressions to a manually chosen reference expression. Anchor frames are automatically computed over one or even multiple performances. We introduce a robust image-space tracking method that computes pixel matches directly from the reference frame to all anchor frames, and thereby to the remaining frames in the sequence via sequential matching. This allows us to propagate one reconstructed frame to an entire sequence in parallel, in contrast to previous sequential methods. Our anchored reconstruction approach also limits tracker drift and robustly handles occlusions and motion blur. The parallel tracking and mesh propagation offer low computation times. Our technique will even automatically match anchor frames across different sequences captured on different occasions, propagating a single mesh to all performances.