High-fidelity facial performance capture with non-sequential temporal alignment

Author(s):  
Martin Klaudiny ◽  
Adrian Hilton
Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3029
Author(s):  
Chen Liu ◽  
Anna Wang ◽  
Chunguang Bu ◽  
Wenhui Wang ◽  
Haijing Sun

High-quality and complete human motion 4D reconstruction is of great significance for immersive VR and even human operation. However, it has inevitable self-scanning constraints, and tracking under monocular settings also has strict restrictions. In this paper, we propose a human motion capture system combined with human priors and performance capture that only uses a single RGB-D sensor. To break the self-scanning constraint, we generated a complete mesh only using the front view input to initialize the geometric capture. In order to construct a correct warping field, most previous methods initialize their systems in a strict way. To maintain high fidelity while increasing the easiness of the system, we updated the model while capturing motion. Additionally, we blended in human priors in order to improve the reliability of model warping. Extensive experiments demonstrated that our method can be used more comfortably while maintaining credible geometric warping and remaining free of self-scanning constraints.


2015 ◽  
Vol 34 (4) ◽  
pp. 1-9 ◽  
Author(s):  
Chen Cao ◽  
Derek Bradley ◽  
Kun Zhou ◽  
Thabo Beeler

2018 ◽  
Vol 17 (3) ◽  
pp. 155-160 ◽  
Author(s):  
Daniel Dürr ◽  
Ute-Christine Klehe

Abstract. Faking has been a concern in selection research for many years. Many studies have examined faking in questionnaires while far less is known about faking in selection exercises with higher fidelity. This study applies the theory of planned behavior (TPB; Ajzen, 1991 ) to low- (interviews) and high-fidelity (role play, group discussion) exercises, testing whether the TPB predicts reported faking behavior. Data from a mock selection procedure suggests that candidates do report to fake in low- and high-fidelity exercises. Additionally, the TPB showed good predictive validity for faking in a low-fidelity exercise, yet not for faking in high-fidelity exercises.


2019 ◽  
Vol 12 (1) ◽  
pp. 18-33 ◽  
Author(s):  
Horea Pauna ◽  
Pierre-Majorique Léger ◽  
Sylvain Sénécal ◽  
Marc Fredette ◽  
Élise Labonté-Lemoyne ◽  
...  

1998 ◽  
Author(s):  
R. Hampton ◽  
Nagendra Subba Rao ◽  
Young Kim ◽  
William Wagar ◽  
Allen Karchmer

2021 ◽  
Author(s):  
Jian Xiao ◽  
Phillip Liu ◽  
D.C. Pham ◽  
Jim Lua ◽  
Shenal Perera ◽  
...  

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