TY - GEN
T1 - Using the orthographic projection model to approximate the perspective projection model for 3D facial reconstruction
AU - Wu, Jin Yi
AU - Lien, Jenn Jier James
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2007
Y1 - 2007
N2 - This study develops a 3D facial reconstruction system, which consists of five modules, using the orthographic projection model to approximate the perspective projection model. The first module identifies a number of feature points on the face and tracks these feature points over a sequence of facial images by the optical flow technique. The second module applies the factorization method to the orthographic model to reconstruct a 3D human face. The facial images are acquired using a pinhole camera, which are based on a perspective projection model. However, the face is reconstructed using an orthographic projection model. To compensate for the difference between these two models, the third module implements a simple and efficient method for approximating the perspective projection model. The fourth module overcomes the missing point problem, commonly arising in 3D reconstruction applications. Finally, the fifth module implements a smoothing process for the 3D surface by interpolating additional vertices.
AB - This study develops a 3D facial reconstruction system, which consists of five modules, using the orthographic projection model to approximate the perspective projection model. The first module identifies a number of feature points on the face and tracks these feature points over a sequence of facial images by the optical flow technique. The second module applies the factorization method to the orthographic model to reconstruct a 3D human face. The facial images are acquired using a pinhole camera, which are based on a perspective projection model. However, the face is reconstructed using an orthographic projection model. To compensate for the difference between these two models, the third module implements a simple and efficient method for approximating the perspective projection model. The fourth module overcomes the missing point problem, commonly arising in 3D reconstruction applications. Finally, the fifth module implements a smoothing process for the 3D surface by interpolating additional vertices.
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U2 - 10.1007/978-3-540-77129-6_41
DO - 10.1007/978-3-540-77129-6_41
M3 - Conference contribution
AN - SCOPUS:38149038591
SN - 9783540771289
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 462
EP - 473
BT - Advances in Image and Video Technology - Second Pacific Rim Symposium, PSIVT 2007, Proceedings
PB - Springer Verlag
T2 - 2nd Pacific Rim Symposium on Image and Video Technology, PSIVT 2007
Y2 - 17 December 2007 through 19 December 2007
ER -