Reshaping 3D facial scans for facial appearance modeling and 3D facial expression analysis

Huang, Yanhui; Zhang, Xing; Fan, Yangyu; Liu, Yin; Seversky, Lee M.; Allen, James F.; Tao, Linmi; Dong, Wei

doi:10.1016/j.imavis.2011.12.008

Cited by 19 publications

(2 citation statements)

References 19 publications

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“…Then, the 3D morphable model was fitted for each input image, and the shape and texture parameters were then reconstructed based on the analysis-by-synthesis framework for performing face recognition. Moreover, Huang et al [12] proposed an efficient method for representing facial shapes from face scans through the reconstruction of face models based on regional data and a generic model. The accuracy of the models was validated through performing 3D facial expression recognition utilising the static 3DFE and dynamic 4DFE databases.…”

Section: Introductionmentioning

confidence: 99%

Real‐world gender classification via local Gabor binary pattern and three‐dimensional face reconstruction by generic elastic model

Moeini¹,

Faez²,

Moeini

2015

IET Image Processing

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In this study, a novel method is proposed for gender classification by adding facial depth features to texture features. Accordingly, the three-dimensional (3D) generic elastic model is used to reconstruct the 3D model from human face using only a single 2D frontal image. Then, the texture and depth are extracted from the reconstructed face model. Afterwards, the local Gabor binary pattern (LGBP) is applied to both facial texture and reconstructed depth to extract the feature vectors from both texture and reconstructed depth images. Finally, by combining 2D and 3D feature vectors, the final LGBP histogram bins are generated and classified by the support vector machine. Favourable outcomes are acquired for gender classification on the labelled faces in the wild and FERET databases based on the proposed method compared to several state-of-the-arts in gender classification.

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Section: Introductionmentioning

confidence: 99%

Real‐world gender classification via local Gabor binary pattern and three‐dimensional face reconstruction by generic elastic model

Moeini¹,

Faez²,

Moeini

2015

IET Image Processing

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“…This is due to several reasons including pose-insensitive face recognition, 1-6 synthesizing new face images from a frontal two-dimensional (2-D) image, 7 facial appearance modeling and 3-D facial expression (FE) analysis, 8 age-insensitive face recognition, 9 etc. Research topics in this field include obtaining shapes from X (SFX), in which X involves shading, texture, focus, stereo, motion, etc.…”

Section: Introductionmentioning

confidence: 99%

Expression-invariant three-dimensional face reconstruction from a single image by facial expression generic elastic models

Moeini

Faez

Moeini

2014

J. Electron. Imaging

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An efficient method for expression-invariant three-dimensional (3-D) face reconstruction from a frontal face image with a variety of facial expressions (FE) using the FE generic elastic model (GEM) is proposed. Three generic models are employed for FE modeling in the generic elastic model (GEM) framework, which are combined based on the similarity distance around the lips. Exclusively, FE-GEM demonstrated that it is more precisely able to estimate a 3-D model of a frontal face, attaining a more robust and better quality 3-D face reconstruction under a variety of FEs compared to the original GEM approach. It is tested on an available 3-D face database and its accuracy and robustness are demonstrated compared to the GEM approach under a variety of FEs. Also, the FE-GEM method is tested on available two-dimensional face databases and a new synthesized pose is generated from gallery images for handling pose variations in face recognition.

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Mobile Apps for 3D Face Scanning

Dzelzkaleja

Knēts

Rozenovskis

et al. 2021

Lecture Notes in Networks and Systems

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Reshaping 3D facial scans for facial appearance modeling and 3D facial expression analysis

Cited by 19 publications

References 19 publications

Real‐world gender classification via local Gabor binary pattern and three‐dimensional face reconstruction by generic elastic model

Real‐world gender classification via local Gabor binary pattern and three‐dimensional face reconstruction by generic elastic model

Expression-invariant three-dimensional face reconstruction from a single image by facial expression generic elastic models

Mobile Apps for 3D Face Scanning

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