3-D motion estimation from motion field
Artificial Intelligence - Special volume on computer vision
Rank-deficient and discrete ill-posed problems: numerical aspects of linear inversion
Rank-deficient and discrete ill-posed problems: numerical aspects of linear inversion
Real-time 3D model acquisition
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Articulated body deformation from range scan data
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Modeling and Rendering for Realistic Facial Animation
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Spacetime-Coherent Geometry Reconstruction from Multiple Video Streams
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Weighted Minimal Hypersurface Reconstruction
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ACM Transactions on Graphics (TOG)
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Dynamic shape capture using multi-view photometric stereo
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Global registration of dynamic range scans for articulated model reconstruction
ACM Transactions on Graphics (TOG)
Temporally coherent completion of dynamic shapes
ACM Transactions on Graphics (TOG)
Animation cartography—intrinsic reconstruction of shape and motion
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Tracking surfaces with evolving topology
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ACM Transactions on Graphics (TOG)
ACM Transactions on Graphics (TOG)
Iterative cage-based registration from multi-view silhouettes
Proceedings of the 10th European Conference on Visual Media Production
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We introduce a volumetric space-time technique for the reconstruction of moving and deforming objects from point data. The output of our method is a four-dimensional space-time solid, made up of spatial slices, each of which is a three-dimensional solid bounded by a watertight manifold. The motion of the object is described as an incompressible flow of material through time. We optimize the flow so that the distance material moves from one time frame to the next is bounded, the density of material remains constant, and the object remains compact. This formulation overcomes deficiencies in the acquired data, such as persistent occlusions, errors, and missing frames. We demonstrate the performance of our flow-based technique by reconstructing coherent sequences of watertight models from incomplete scanner data.