CLC number: TP319
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2017-12-20
Cited: 0
Clicked: 5958
Feng Liu, Dan Zeng, Jing Li, Qi-jun Zhao. On 3D face reconstruction via cascaded regression in shape space[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(12): 1978-1990.
@article{title="On 3D face reconstruction via cascaded regression in shape space",
author="Feng Liu, Dan Zeng, Jing Li, Qi-jun Zhao",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="18",
number="12",
pages="1978-1990",
year="2017",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1700253"
}
%0 Journal Article
%T On 3D face reconstruction via cascaded regression in shape space
%A Feng Liu
%A Dan Zeng
%A Jing Li
%A Qi-jun Zhao
%J Frontiers of Information Technology & Electronic Engineering
%V 18
%N 12
%P 1978-1990
%@ 2095-9184
%D 2017
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1700253
TY - JOUR
T1 - On 3D face reconstruction via cascaded regression in shape space
A1 - Feng Liu
A1 - Dan Zeng
A1 - Jing Li
A1 - Qi-jun Zhao
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 18
IS - 12
SP - 1978
EP - 1990
%@ 2095-9184
Y1 - 2017
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1700253
Abstract: Cascaded regression has been recently applied to reconstruct 3D faces from single 2D images directly in shape space, and has achieved state-of-the-art performance. We investigate thoroughly such cascaded regression based 3D face reconstruction approaches from four perspectives that are not well been studied: (1) the impact of the number of 2D landmarks; (2) the impact of the number of 3D vertices; (3) the way of using standalone automated landmark detection methods; (4) the convergence property. To answer these questions, a simplified cascaded regression based 3D face reconstruction method is devised. This can be integrated with standalone automated landmark detection methods and reconstruct 3D face shapes that have the same pose and expression as the input face images, rather than normalized pose and expression. An effective training method is also proposed by disturbing the automatically detected landmarks. Comprehensive evaluation experiments have been carried out to compare to other 3D face reconstruction methods. The results not only deepen the understanding of cascaded regression based 3D face reconstruction approaches, but also prove the effectiveness of the proposed method.
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