Fast Model-based 3D Human Face Reconstruction from Silhouettes of Multiple Views

2006 ◽  
Author(s):  
Yat-Cheung Wong ◽  
W.H. Lau
Keyword(s):  
Multiple Views ◽  
Human Face ◽  
Face Reconstruction ◽  
Model Based

Age and gender-based human face reconstruction from single frontal image

2018 ◽  
Vol 79 (5-6) ◽  
pp. 3217-3242 ◽  
Author(s):  
Zuzana Ferková ◽  
Petra Urbanová ◽  
Dominik Černý ◽  
Marek Žuži ◽  
Petr Matula
Keyword(s):  
Human Face ◽  
Age And Gender ◽  
Face Reconstruction ◽  
Gender Based ◽  
And Gender

scholarly journals Model-based human shape reconstruction from multiple views

2008 ◽  
Vol 111 (2) ◽  
pp. 179-194 ◽  
Author(s):  
Jonathan Starck ◽  
Adrian Hilton
Keyword(s):  
Shape Reconstruction ◽  
Multiple Views ◽  
Model Based

3D model-based pose invariant face recognition from multiple views

2007 ◽  
Vol 1 (1) ◽  
pp. 25-34 ◽  
Author(s):  
Q. Chen ◽  
J. Yao ◽  
W.K. Cham
Keyword(s):  
Face Recognition ◽  
3D Model ◽  
Multiple Views ◽  
Model Based

Urban Noise Inference Model Based on Multiple Views and Kernel Tensor Decomposition

2021 ◽  
pp. 2150027
Author(s):  
Junlan Nie ◽  
Ruibo Gao ◽  
Ye Kang
Keyword(s):  
Noise Pollution ◽  
Tensor Decomposition ◽  
Prediction Algorithm ◽  
Kernel Matrix ◽  
Multiple Views ◽  
Tensor Factorization ◽  
Urban Noise ◽  
Model Based ◽  
Factorization Model ◽  
Kernel Distance

Prediction of urban noise is becoming more significant for tackling noise pollution and protecting human mental health. However, the existing noise prediction algorithms neglected not only the correlation between noise regions, but also the nonlinearity and sparsity of the data, which resulted in low accuracy of filling in the missing entries of data. In this paper, we propose a model based on multiple views and kernel-matrix tensor decomposition to predict the noise situation at different times of day in each region. We first construct a kernel tensor decomposition model by using kernel mapping in order to speed decomposition rate and realize stable estimate the prediction system. Then, we analyze and compute the cause of the noise from multiple views including computing the similarity of regions and the correlation between noise categories by kernel distance, which improves the credibility to infer the noise situation and the categories of regions. Finally, we devise a prediction algorithm based on the kernel-matrix tensor factorization model. We evaluate our method with a real dataset, and the experiments to verify the advantages of our method compared with other existing baselines.

Accuracy enhancement of 3D profilometric human face reconstruction using undecimated wavelet analysis

2012 ◽  
Vol 51 (16) ◽  
pp. 3120 ◽  
Author(s):  
Fatemeh Mohammadi ◽  
Khosro Madanipour ◽  
Amir Hossein Rezaie
Keyword(s):  
Wavelet Analysis ◽  
Human Face ◽  
Accuracy Enhancement ◽  
Face Reconstruction ◽  
Undecimated Wavelet
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