Spacetime faces: high resolution capture for modeling and animation

By Li Zhang, Noah Snavely, Brian Curless, S. M. Seitz. ACM Transactions on Graphics, 2004

641 citations recorded by the source corpus.

Subfields: Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/b2c2f2cd5c5d80f743cbe9559917e076ca9146e3

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In Computer Graphics and Computer-Aided Design

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In Control and Systems Engineering

Citations in the corpus

Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid (2013, neutral): “correspondences [23], [29], [32], [34], [80].”
Internet Based Morphable Model (2013, methodology): “Similarly we collected photos of adults making different facial expressions.”
RGBD Datasets: Past, Present and Future (2016, methodology): “Early face datasets focused on the method of acquisition (e.g. [118]) or tended to be quite small (e.g. [13]).”
Recent progresses on real-time 3D shape measurement using digital fringe projection techniques (2010, methodology): “Spacetime stereo is another technique that has potential for high speed 3D shape measurement [2] [3] [4].”
A Survey on Human Motion Analysis from Depth Data (2013, background): “Most of the work has focused so far on the acquisition of high-quality data using structured light systems [100, 101, 102, 103, 104] or passive multi-camera systems [105, 106, 101, 107] in controlled setups.”
Production-level facial performance capture using deep convolutional neural networks (2016, background): “…[Alexander et al. 2009; Beeler et al. 2011; Bhat et al. 2013; Borshukov et al. 2005; Fyffe et al. 2014; Vlasic et al. 2005; Weise et al. 2009a; Zhang et al. 2004] and a considerable amount of computation such as multi-view stereo or photometric reconstruction of individual input frames…”
A FACS valid 3D dynamic action unit database with applications to 3D dynamic morphable facial modeling (2011, methodology): “Figure 3 shows examples of how the LK error accumulates over the course of tracking, supporting the optical flow drift observations in [6, 7, 24].”
Dense one-shot 3D reconstruction by detecting continuous regions with parallel line projection (2011, methodology): “Some methods use projectors only to provide textures that change over time and 3D information is restored us ing a passive stereo technique [6, 24], although they are not strictly structured light systems.”
Fast 3D Scanning with Automatic Motion Compensation (2007, neutral): “[20, 21] use oriented spacetime windows to deal with motion.”
Mesh-based inverse kinematics (2005, methodology): “FaceIK [Zhang et al. 2004] uses a similar approach on meshes to generate new facial expressions by linearly blending the acquired face scans.”
Real-time expression transfer for facial reenactment (2015, background): “Dynamic active 3D scanners, for instance based on structured light projectors, also provide high-quality data which has been used to capture facial performances [Zhang et al. 2004; Wang et al. 2004; Weise et al. 2009].”
A deep learning approach for generalized speech animation (2017, neutral): “The main alternative to hand animation is performance-driven animation using facial motion capture of an actor’s face [Beeler et al. 2011; Cao et al. 2015, 2013; Fyffe et al. 2014; Huang et al. 2011; Li et al. 2013; Weise et al. 2011; Weng et al. 2014; Zhang et al. 2004].”
3D Morphable Face Models—Past, Present, and Future (2019, positive): “Active systems have been considered, both geometric [Zhang et al. 2004] and photometric [Wilson et al. 2010].”