@article{251b5adbdb7a4c6aad93453a3fecce6f,
title = "Annotated face model-based alignment: a robust landmark-free pose estimation approach for 3D model registration",
abstract = "Registering a 3D facial model onto a 2D image is important for constructing pixel-wise correspondences between different facial images. The registration is based on a 3 × 4 dimensional projection matrix, which is obtained from pose estimation. Conventional pose estimation approaches employ facial landmarks to determine the coefficients inside the projection matrix and are sensitive to missing or incorrect landmarks. In this paper, a landmark-free pose estimation method is presented. The method can be used to estimate the matrix when facial landmarks are not available. Experimental results show that the proposed method outperforms several landmark-free pose estimation methods and achieves competitive accuracy in terms of estimating pose parameters. The method is also demonstrated to be effective as part of a 3D-aided face recognition pipeline (UR2D), whose rank-1 identification rate is competitive to the methods that use landmarks to estimate head pose.",
keywords = "Face alignment, Face recognition, Model registration, Pose estimation",
author = "Yuhang Wu and Shah, {Shishir K.} and Kakadiaris, {Ioannis A.}",
note = "Funding Information: Roy and Lillie Cranz Cullen University Professor of Com- puter Science, Electrical & Com- puter Engineering, and Biomedi- cal Engineering at the University of Houston. He joined UH in 1997 after a postdoctoral fellow- ship at the University of Penn- sylvania. He earned his B.Sc. in physics at the University of Athens in Greece, his M.Sc. in computer science from North- eastern University and his Ph.D. at the University of Pennsylva nia. He is the founder of the Computational Biomedicine Lab and the Director of the DHS Center of Excellence on Borders, Trade, and Immigration Research (BTI). His research interests include biometrics, video analytics, computer vision, pattern recognition, and biomedical image computing. He is the recipient of a number of awards, including the NSF Early Career Development Award, Schlumberger Technical Foundation Award, UH Computer Science Research Excellence Award, UH Enron Teaching Excellence Award, and the James Muller Vulnerable Plaque Young Investigator Prize. His research has been featured on The Discovery Channel, National Public Radio, KPRC NBC News, KTRH ABC News, and KHOU CBS News. Funding Information: This material is based upon work supported by the U.S. Department of Homeland Security under Grant Award Number 2015-ST-061-BSH001. This grant is awarded to the Borders, Trade, and Immigration (BTI) Institute: A DHS Center of Excellence led by the University of Houston, and includes support for the project “Image and Video Person Identification in an Operational Environment: Phase I” awarded to the University of Houston. The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the U.S. Department of Homeland Security. Publisher Copyright: {\textcopyright} 2017, Springer-Verlag GmbH Germany.",
year = "2018",
month = apr,
day = "1",
doi = "10.1007/s00138-017-0887-6",
language = "English (US)",
volume = "29",
pages = "375--391",
journal = "Machine Vision and Applications",
issn = "0932-8092",
publisher = "Springer Verlag",
number = "3",
}