Reconstructing 3D face shapes from single 2D images using an adaptive deformation model

The Representational Power (RP) of an example-based model is its capability to depict a new 3D face for a given 2D face image. In this contribution, a novel approach is proposed to increase the RP of the 3D reconstruction PCA-based model by deforming a set of examples in the training dataset. By adding these deformed samples together with the original training samples we gain more RP. A 3D PCA-based model is adapted for each new input face image by deforming 3D faces in the training data set. This adapted model is used to reconstruct the 3D face shape for the given input 2D near frontal face image. Our experimental results justify that the proposed adaptive model considerably improves the RP of the conventional PCA-based model

Appl Ergon

The objective of this study was to quantify head-and-face shape variations of U.S. civilian workers using modern methods of shape analysis. The purpose of this study was based on previously highlighted changes in U.S. civilian worker head-and-face shape over the last few decades - touting the need for new and better fitting respirators - as well as the study's usefulness in designing more effective personal protective equipment (PPE) - specifically in the field of respirator design. The raw scan three-dimensional (3D) data for 1169 subjects were parameterized using geometry processing techniques. This process allowed the individual scans to be put in correspondence with each other in such a way that statistical shape analysis could be performed on a dense set of 3D points. This process also cleaned up the original scan data such that the noise was reduced and holes were filled in. The next step, statistical analysis of the variability of the head-and-face shape in the 3D database, was conducted using Principal Component Analysis (PCA) techniques. Through these analyses, it was shown that the space of the head-and-face shape was spanned by a small number of basis vectors. Less than 50 components explained more than 90% of the variability. Furthermore, the main mode of variations could be visualized through animating the shape changes along the PCA axes with computer software in executable form for Windows XP. The results from this study in turn could feed back into respirator design to achieve safer, more efficient product style and sizing. Future study is needed to determine the overall utility of the point cloud-based approach for the quantification of facial morphology variation and its relationship to respirator performance.CC999999/Intramural CDC HHS/United States2016-02-09T00:00:00Z23399025PMC474703

J Occup Environ Hyg

The contact area, as well as the contact pressure, is created when a respiratory protection device (a respirator or surgical mask) contacts a human face. A computer-based algorithm for determining the contact area between a headform and N95 filtering facepiece respirator (FFR) was proposed. Six N95 FFRs were applied to five sizes of standard headforms (large, medium, small, long/narrow, and short/wide) to simulate respirator donning. After the contact simulation between a headform and an N95 FFR was conducted, a contact area was determined by extracting the intersection surfaces of the headform and the N95 FFR. Using computer-aided design tools, a superimposed contact area and an average contact area, which are non-uniform rational basis spline (NURBS) surfaces, were developed for each headform. Experiments that directly measured dimensions of the contact areas between headform prototypes and N95 FFRs were used to validate the simulation results. Headform sizes influenced all contact area dimensions (P < 0.0001), and N95 FFR sizing systems influenced all contact area dimensions (P < 0.05) except the left and right chin regions. The medium headform produced the largest contact area, while the large and small headforms produced the smallest.CC999999/Intramural CDC HHS/United States254-2009-M-31878/PHS HHS/United States254-2010-M-36735/PHS HHS/United States254-2012-M-52258/PHS HHS/United States2016-02-09T00:00:00Z24579752PMC4747037763

Adaptive face modelling for reconstructing 3D face shapes from single 2D images

Example-based statistical face models using principle component analysis (PCA) have been widely deployed for three-dimensional (3D) face reconstruction and face recognition. The two common factors that are generally concerned with such models are the size of the training dataset and the selection of different examples in the training set. The representational power (RP) of an example-based model is its capability to depict a new 3D face for a given 2D face image. The RP of the model can be increased by correspondingly increasing the number of training samples. In this contribution, a novel approach is proposed to increase the RP of the 3D face reconstruction model by deforming a set of examples in the training dataset. A PCA-based 3D face model is adapted for each new near frontal input face image to reconstruct the 3D face shape. Further an extended Tikhonov regularisation method has been

Comparative analysis of facial morphology between Okinawa Islanders and mainland Japanese using three-dimensional images.

OBJECTIVES: Differences in facial height and breadth between Okinawa Islanders and mainland Japanese have been reported in previous craniometric and somatometric studies. This study using three-dimensional (3D) images aimed to identify more detailed characteristics of facial morphology in each population. METHODS: Using a hand-held 3D scanner, we obtained 60 facial surface images each from Okinawa Islanders and mainland Japanese. Twenty-one landmarks were plotted on a computer and 27 measurements of distances and angles between the landmarks were taken. Statistical analyses such as t test, principal component analysis (PCA), regression analysis, and discriminant analysis were performed to identify sex and regional differences, the patterns of facial features, factors explaining the facial patterns, and other features. RESULTS: Okinawa Islanders showed lower facial and nasal heights than mainland Japanese. Furthermore, we identified larger protrusions of the glabella and nasal root in Okinawa Islanders than in mainland Japanese. In the PCA, we observed components of facial shape patterns. These components mainly represented facial size (PC1), facial depth (PC2), the prominence of the glabella and nasal root (PC3), and facial breadth (PC4). We identified that the population difference is strongly associated with PC3. CONCLUSIONS: This study quantitatively identified differences in the facial morphology between Okinawa Islanders and mainland Japanese using 3D digital images, with special emphases on the differences in the nasal height and the prominence of the glabella and nasal root

Ann Occup Hyg

This study aims to elucidate variations in head-and-face shape among the Chinese civilian workers. Most respirator manufacturers are using outdated, Western anthropometric data to design respirators for the Chinese workers. Therefore, newly acquired anthropometric data specific to the Chinese population are needed to create more effective personal protective equipment. The three-dimensional (3D) head scans of 350 participants, who were selected from the 3000 participants in the 2006 Chinese Anthropometric Survey, were processed using geometric processing techniques. Each scan was then linked with the others, making statistical shape analysis on a dense set of 3D points possible. Furthermore, this provided for the reduction of scan noise as well as for the patching of holes. Following general scan correspondence and fine tuning, principal component analysis was used to analyze the variability in head-and-face shape of the 3D images. More than 90% of the variability among head-and-face shapes was accounted for with 26 principal components. Future study is recommended so the overall usefulness of the point cloud-based approach for the quantification of variations in facial morphology may be determined.20152017-07-11T00:00:00ZCC999999/Intramural CDC HHS/United States25858431PMC5504517711

A parametric product design framework for the development of mass customized head/face (Eyewear) products

This study led to the development of a parametric design method for mass-customised head/face products. A systematic review of different approaches for mass customization was conducted, identifying advantages and limitations for their application to new product development. A parametric modelling algorithm of a 3D human face was developed using selected scanned 3D head models. The algorithm was developed from a set of measurable and adjustable parameter points related to the facial geometry. These parameters were defined using planimetry. Using the assigned parameter values as input, the parametric model generated 3D models of a human face that served as a reference for the design of customized eyewear. The current challenges and opportunities of mass customized head/face products are described, along with the possibilities for new parametric product design approaches to enable rapid manufacturing and mass customization. This study also explored whether a new parametric design framework for mass customization could be effectively implemented as an early-stage new product development strategy for head/face products