"Trapezoidal phase-shifting method for three-dimensional shape measurement," Opt. Eng., (2005)

[2] PS Huang, S Zhang, and F-P Chiang, "Trapezoidal phase-shifting method for three-dimensional shape measurement," Opt. Eng. 44(12), 123601, 2005; doi:10.1117/1.2147311

We propose a novel structured light method, namely a trapezoidal phase-shifting method, for 3-D shape measurement. This method uses three patterns coded with phase-shifted, trapezoidalshaped gray levels. The 3-D information of the object is extracted by direct calculation of an intensity ratio. Compared to traditional intensityratio-based methods, the vertical or depth resolution is six times better. Also, this new method is significantly less sensitive to the defocusing effect of the captured images, which makes large-depth 3-D shape measurement possible. If compared to sinusoidal phase-shifting methods, the resolution is similar, but the data processing speed is at least 4.5 times faster. The feasibility of this method is demonstrated in a previously developed real-time 3-D shape measurement system. The reconstructed 3-D results show similar quality to those obtained by the sinusoidal phase-shifting method. However, since the data processing speed is much faster
4.6 ms per frame, both image acquisition and 3-D reconstruction can be done in real time at a frame rate of 40 fps and a resolution of 532
500 points. This real-time capability allows us to measure dynamically changing objects, such as human faces. The potential applications of this new method include industrial inspection, reverse engineering, robotic vision, computer graphics, medical diagnosis, etc. 

"High-resolution acquisition, learning and transfer dynamic 3D facial expressions," Computer Graphics Forum, (2004)

[1] Y Wang, X Huang, C-S Lee, S Zhang, Z Li, D Samaras, D Metaxas, A Elgammal, and P Huang, "High-resolution acquisition, learning and transfer dynamic 3D facial expressions," Computer Graphics Forum, 23(3), 2004; doi: 10.1111/j.1467-8659.2004.00800.x

Synthesis and re-targeting of facial expressions is central to facial animation and often involves significant manual work in order to achieve realistic expressions, due to the difficulty of capturing high quality dynamic expression data. In this paper we address fundamental issues regarding the use of high quality dense 3-D data samples undergoing motions at video speeds, e.g. human facial expressions. In order to utilize such data for motion analysis and re-targeting, correspondences must be established between data in different frames of the same faces as well as between different faces. We present a data driven approach that consists of four parts: 1) High speed, high accuracy capture of moving faces without the use of markers, 2) Very precise tracking of facial motion using a multi-resolution deformable mesh, 3) A unified low dimensional mapping of dynamic facial motion that can separate expression style, and 4) Synthesis of novel expressions as a combination of expression styles. The accuracy and resolution of our method allows us to capture and track subtle expression details. The low dimensional representation of motion data in a unified embedding for all the subjects in the database allows for learning the most discriminating characteristics of each individual’s expressions as that person’s “expression style”. Thus new expressions can be synthesized, either as dynamic morphing between individuals, or as expression transfer from a source face to a target face, as demonstrated in a series of experiments.