Advancing Wound Filling Extraction on 3D Faces:An Auto-Segmentation and Wound Face Regeneration Approach

Facial wound segmentation plays a crucial role in preoperative planning and optimizing patient outcomes in various medical applications.In this paper,we propose an efficient approach for automating 3D facial wound segmentation using a two-stream graph convolutional network.Our method leverages the Cir3D-FaIR dataset and addresses the challenge of data imbalance through extensive experimentation with different loss functions.To achieve accurate segmentation,we conducted thorough experiments and selected a high-performing model from the trainedmodels.The selectedmodel demonstrates exceptional segmentation performance for complex 3D facial wounds.Furthermore,based on the segmentation model,we propose an improved approach for extracting 3D facial wound fillers and compare it to the results of the previous study.Our method achieved a remarkable accuracy of 0.9999993% on the test suite,surpassing the performance of the previous method.From this result,we use 3D printing technology to illustrate the shape of the wound filling.The outcomes of this study have significant implications for physicians involved in preoperative planning and intervention design.By automating facial wound segmentation and improving the accuracy ofwound-filling extraction,our approach can assist in carefully assessing and optimizing interventions,leading to enhanced patient outcomes.Additionally,it contributes to advancing facial reconstruction techniques by utilizing machine learning and 3D bioprinting for printing skin tissue implants.Our source code is available at https://github.com/SIMOGroup/WoundFilling3D.

Generating animatable 3D cartoon faces from single portraits

Background With the development of virtual reality(VR)technology,there is a growing need for customized 3D avatars.However,traditional methods for 3D avatar modeling are either time-consuming or fail to retain the similarity to the person being modeled.This study presents a novel framework for generating animatable 3D cartoon faces from a single portrait image.Methods First,we transferred an input real-world portrait to a stylized cartoon image using StyleGAN.We then proposed a two-stage reconstruction method to recover a 3D cartoon face with detailed texture.Our two-stage strategy initially performs coarse estimation based on template models and subsequently refines the model by nonrigid deformation under landmark supervision.Finally,we proposed a semantic-preserving face-rigging method based on manually created templates and deformation transfer.Conclusions Compared with prior arts,the qualitative and quantitative results show that our method achieves better accuracy,aesthetics,and similarity criteria.Furthermore,we demonstrated the capability of the proposed 3D model for real-time facial animation.

Face recognition using SIFT features under 3D meshes

Expression, occlusion, and pose variations are three main challenges for 3D face recognition. A novel method is presented to address 3D face recognition using scale-invariant feature transform(SIFT) features on 3D meshes. After preprocessing, shape index extrema on the 3D facial surface are selected as keypoints in the difference scale space and the unstable keypoints are removed after two screening steps. Then, a local coordinate system for each keypoint is established by principal component analysis(PCA).Next, two local geometric features are extracted around each keypoint through the local coordinate system. Additionally, the features are augmented by the symmetrization according to the approximate left-right symmetry in human face. The proposed method is evaluated on the Bosphorus, BU-3DFE, and Gavab databases, respectively. Good results are achieved on these three datasets. As a result, the proposed method proves robust to facial expression variations, partial external occlusions and large pose changes.

Technologically Advanced Reusable 3D Face Shield for Health Workers Confronting COVID19

The probability of medical staff to get affected from COVID19 is much higher due to their working environment which is more exposed to infectious diseases.So,as a preventive measure the body temperature monitoring of medical staff at regular intervals is highly recommended.Infrared temperature sensing guns have proved its effectiveness and therefore such devices are used to monitor the body temperature.These devices are either used on hands or forehead.As a result,there are many issues in monitoring the temperature of frontline healthcare professionals.Firstly,these healthcare professionals keep wearing PPE(Personal Protective Equipment)kits during working hours and as a result it would be very difficult to monitor their body temperature.Secondly,these healthcare professionals also wear face shields and in such cases monitoring temperature by exposing forehead needs removal of face shield.Doing so after regular intervals is surely uncomfortable for healthcare professionals.To avoid such issues,this paper is disclosing a technologically advanced face shield equipped with sensors capable of monitoring body temperature instantly without the hassle of removing the face shield.This face shield is integrated with a built-in infrared temperature sensor.A total of 10 such face shields were printed and assembled within the university lab and then handed over to a group of ten members including faculty and students of nursing and health science department.This sequence was repeated four times and as a result 40 healthcare workers participated in the study.Thereafter,feedback analysis was conducted on questionnaire data and found a significant overall mean score of 4.59 out of 5 which indicates that the product is effective and worthy in every facet.Stress analysis is also performed in the simulated environment and found that the device can easily withstand the typically applied forces.The limitations of this product are difficulty in cleaning the product and comparatively high cost due to the deployment of electronic equipment.

Research on 3D Modeling and Visualization of Coal Pillars for Surface Protection

In order to safely exploit coal resource, protection coal pillars must be prepared in coal mines. Some correlative parameters of protection coal pillar are calculated by Drop face and Drop line methods. Models of protecting surface objects and coal pillars are established by TIN modeling and object-oriented technique. By using ACCESS2000as the database and the VC＋＋ and OpenGL as the language, the calculation of protective coal pillars is realized and the 3D-visulizaiton system for protected objects on ground surface and for coal pillars is developed. The system can obtain the data of characteristic points on the surface interactively from the digitized mine topography map, constructing 3D model automatically. It can also obtain the interrelated parameters of the coal seam and drill hole data from existing geolog!cal surveying database to calculate the location, surface area and the total coal columns. The whole process can be computed quickly and accurately. And the 3D visualization system was applied in a mine, showing that the system solve the problem of complex calculation, not only realized the automatic 3D mapping and visualization of coal pillars for buildings protection, but also greatly improves the working efficiency.

Measuring 3D face deformations from RGB images of expression rehabilitation exercises

Background The accurate(quantitative)analysis of 3D face deformation is a problem of increasing interest in many applications.In particular,defining a 3D model of the face deformation into a 2D target image to capture local and asymmetric deformations remains a challenge in existing literature.A measure of such local deformations may be a relevant index for monitoring the rehabilitation exercises of patients suffering from Par-kinson’s or Alzheimer’s disease or those recovering from a stroke.Methods In this paper,a complete framework that allows the construction of a 3D morphable shape model(3DMM)of the face is presented for fitting to a target RGB image.The model has the specific characteristic of being based on localized components of deformation.The fitting transformation is performed from 3D to 2D and guided by the correspondence between landmarks detected in the target image and those manually annotated on the average 3DMM.The fitting also has the distinction of being performed in two steps to disentangle face deformations related to the identity of the target subject from those induced by facial actions.Results The method was experimentally validated using the MICC-3D dataset,which includes 11 subjects.Each subject was imaged in one neutral pose and while performing 18 facial actions that deform the face in localized and asymmetric ways.For each acquisition,3DMM was fit to an RGB frame whereby,from the apex facial action and the neutral frame,the extent of the deformation was computed.The results indicate that the proposed approach can accurately capture face deformation,even localized and asymmetric deformations.Conclusion The proposed framework demonstrated that it is possible to measure deformations of a reconstructed 3D face model to monitor facial actions performed in response to a set of targets.Interestingly,these results were obtained using only RGB targets,without the need for 3D scans captured with costly devices.This paves the way for the use of the proposed tool in remote medical rehabilitation monitoring.

An Algorithm for Finding Internal Faces Based on the 3D Coordinates

This paper presents a direct method to find the internal faces. It uses four sets of information： get the coordinates of each point on the 3D composite objects; （~）based on the 3D coordinates to calculate all the plane equation of two objects; （~）calculate all the intersecting lines of the two objects and exclude the intersecting lines which are not within the scope of the plane;finding the internal face, the remaining intersecting lines formed the plane is the internal face of the two objects. We proposed a new algorithm for finding internal faces. This algorithm could be adapted to any regular composite objects .The algorithm works well for finding internal faces.

金佛山混凝土面板堆石坝地震反应3-D分析

基于等效线性模型,采用三维非线性动力有限元法对拟建金佛山混凝土面板堆石坝进行了地震动力反应分析,重点研究了坝体在地震荷载作用下的加速度反应、动应力反应、地震永久变形的规律和分布。计算结果表明:坝顶附近加速度反应较大,应采取相应的抗震工程措施;坝体动应力反应较小;坝体残余变形不大;大坝整体抗震性能较好,满足给定地震下的抗震安全性要求。

Synthesis,Style Editing,and Animation of 3D Cartoon Face

As a popular kind of stylized face,cartoon faces have rich application scenarios.It is challenging to create personalized 3D cartoon faces directly from 2D real photos.Besides,in order to adapt to more application scenarios,automatic style editing,and animation of cartoon faces is also a crucial problem that is urgently needed to be solved in the industry,but has not yet had a perfect solution.To solve this problem,we first propose“3D face cartoonizer”,which can generate high-quality 3D cartoon faces with texture when fed into 2D facial images.We contribute the first 3D cartoon face hybrid dataset and a new training strategy which first pretrains our network with low-quality triplets in a reconstruction-then-generation manner,and then finetunes it with high-quality triplets in an adversarial manner to fully leverage the hybrid dataset.Besides,we implement style editing for 3D cartoon faces based on k-means,which can be easily achieved without retrain the neural network.In addition,we propose a new cartoon faces'blendshape generation method,and based on this,realize the expression animation of 3D cartoon faces,enabling more practical applications.Our dataset and code will be released for future research.

基于球面调和函数的3-D人脸识别方法

根据3-D数据的优势,利用图像成像原理和球面调和函数理论,结合3-D投影原理和PCA技术建立了一个3-D人脸模型。该模型用不受光线影响的低维线性子空间的基向量来表示,将结构和纹理两个3-D信息作为整体进行考虑,使得模型只需要通过一组参数简单描述。由于本文构建的3-D模型只与人脸的内在属性有关,与光线无关,因此能够排除光线对人脸识别率的影响,本文在AR人脸数据库上的识别实验证明了本文方法的有效性。

Application of 3-D Parallel Electrical Technology Detecting the Water-Rich Areas

Coal working face is damaged more and more seriously by water below the coal face floor. Therefore, floor water detection is a must in the process of extraction. This article aims to introducing application and principle of the two-gateways parallel 3-D electrical technology and the arrangement of the observation system. The authors use this method to detect the water under the floor of a mine in north of Anhui. The results show that the two-gateways parallel 3-D electrical technology can accurately locate the water-rich areas, providing the basis for drilling drainage and grouting construction.

全面布局3D视觉应用OPPO下一代新品将搭载TOF技术

8月6日,OPPOTOF技术沟通会在北京召开.沟通会上,OPPO向外界介绍了TOF技术以及OPPO对未来TOF技术发展的理解,同时宣布将会在下一款产品中正式加入TOF技术,成为继实现OPPO Face Key 3D结构光技术大规模量产之后OPPO在3D视觉技术方面的又一重要技术突破.

Visualization Analysis for 3D Big Data Modeling

This paper describes an automatic system for 3D big data of face modeling using front and side view images taken by an ordinary digital camera, whose directions are orthogonal. The paper consists of four keys in 3D visualization. Firstly we study the 3D big data of face modeling including feature facial extraction from 2D images. The second part is to represent the technical from Computer Vision, Image Processing and my new method for extract information from images and create 3D model. Thirdly, 3D face modeling based on 2D image software is implemented by C# language, EMGU CV library and XNA framework. Finally, we design experiment, test and record results for measure performance of our method.

这神器能将自拍秒变3D模型--能骗过iPhone X吗？

今年9月，苹果发布了十周年纪念之作iPhone X，其中的Face ID或许是最受瞩目的一个功能，引发的争议也最大，人们对于这种人脸识别安全性的担忧转化成了段子手的狂欢。

Analysis of Combined Radiation and Forced Convection Heat Transfer in 3D Laminar Flow over an Inclined Forward Facing Step

In the current study, a numerical investigation of three-dimensional combined convection-radiation heat transfer over an inclined forward facing step (FFS) in a horizontal rectangular duct is presented. The fluid is treated as a gray, absorbing, emitting and scattering medium. To simulate the incline surface of FFS, the blocked-off method is employed in this study. The set of governing equations for gas flow are solved numerically using the CFD technique to obtain the temperature and velocity fields. Since the gas is considered as a radiating medium, all of the convection, conduction and radiation heat transfer mechanisms are presented in the energy equation. For computation of radiative term in energy equation, the radiative transfer equation (RTE) is solved numerically by the discrete ordinates method (DOM) to find the divergence of radiative heat flux distribution inside the radiating medium. The effects of optical thickness, radiation-conduction parameter and albedo coefficient on heat transfer behavior of the system are carried out.

三维空间深度位置上情绪面孔对返回抑制的影响

通过虚拟现实技术构建虚拟三维场景,将Posner线索化范式应用到三维空间,通过两个实验操纵了目标深度、线索有效性以及情绪面孔的效价,考察了三维空间深度位置上情绪面孔如何影响视觉空间返回抑制。结果发现,(1)情绪面孔作为目标时,目标出现在近处空间,情绪面孔效价与返回抑制存在交互作用,负性面孔下的返回抑制减小;(2)情绪面孔作为线索时,目标出现在远处空间,情绪面孔效价与返回抑制存在交互作用,负性面孔下的返回抑制增大。研究表明,三维空间中情绪面孔能够影响返回抑制的大小,且这种影响在远近空间下存在差异。

One-shot Face Reenactment with Dense Correspondence Estimation

One-shot face reenactment is a challenging task due to the identity mismatch between source and driving faces.Most existing methods fail to completely eliminate the interference of driving subjects’identity information,which may lead to face shape distortion and undermine the realism of reenactment results.To solve this problem,in this paper,we propose using a 3D morphable model(3DMM)for explicit facial semantic decomposition and identity disentanglement.Instead of using 3D coefficients alone for reenactment control,we take advantage of the generative ability of 3DMM to render textured face proxies.These proxies contain abundant yet compact geometric and semantic information of human faces,which enables us to compute the face motion field between source and driving images by estimating the dense correspondence.In this way,we can approximate reenactment results by warping source images according to the motion field,and a generative adversarial network(GAN)is adopted to further improve the visual quality of warping results.Extensive experiments on various datasets demonstrate the advantages of the proposed method over existing state-of-the-art benchmarks in both identity preservation and reenactment fulfillment.

3D face recognition:A comprehensive survey in 2022

In the past ten years,research on face recognition has shifted to using 3D facial surfaces,as 3D geometric information provides more discriminative features.This comprehensive survey reviews 3D face recognition techniques developed in the past decade,both conventional methods and deep learning methods.These methods are evaluated with detailed descriptions of selected representative works.Their advantages and disadvantages are summarized in terms of accuracy,complexity,and robustness to facial variations(expression,pose,occlusion,etc.).A review of 3D face databases is also provided,and a discussion of future research challenges and directions of the topic.

Sphere Face Model: A 3D morphable model with hypersphere manifold latent space using joint 2D/3D training

3D morphable models(3DMMs)are generative models for face shape and appearance.Recent works impose face recognition constraints on 3DMM shape parameters so that the face shapes of the same person remain consistent.However,the shape parameters of traditional 3DMMs satisfy the multivariate Gaussian distribution.In contrast,the identity embeddings meet the hypersphere distribution,and this conflict makes it challenging for face reconstruction models to preserve the faithfulness and the shape consistency simultaneously.In other words,recognition loss and reconstruction loss can not decrease jointly due to their conflict distribution.To address this issue,we propose the Sphere Face Model(SFM),a novel 3DMM for monocular face reconstruction,preserving both shape fidelity and identity consistency.The core of our SFM is the basis matrix which can be used to reconstruct 3D face shapes,and the basic matrix is learned by adopting a twostage training approach where 3D and 2D training data are used in the first and second stages,respectively.We design a novel loss to resolve the distribution mismatch,enforcing that the shape parameters have the hyperspherical distribution.Our model accepts 2D and 3D data for constructing the sphere face models.Extensive experiments show that SFM has high representation ability and clustering performance in its shape parameter space.Moreover,it produces highfidelity face shapes consistently in challenging conditions in monocular face reconstruction.The code will be released at https://github.com/a686432/SIR.

Pseudo-dynamic analysis of a 3D tunnel face in inclined weak strata

A new discretization technique is proposed for a three-dimensional(3D)tunnel face in weak strata with a random position in space.This method limits the angle,height,and thickness of the strata on the tunnel face.The original whole piece of soil is separated by a series of parallel planes,and two parallel planes are used as a stratum.Each radial discrete plane is separated when it passes through the strata,and the change in the soil properties of discrete points on the truncated plane is considered separately inside the strata.Considering the spatial and temporal characteristics of seismic waves,a pseudo-dynamic analysis of the tunnel face is carried out.The tunnel face active damage types under earthquake conditions are quantitatively analyzed,and the corresponding support pressure design diagrams are given for the case without weak strata.For the case containing weak strata,the presence of weak strata can have adverse effects on the face.The failure mechanism of the weak strata is given by the discretization method.For different friction angles,the presence of the weak strata changes the friction angles of the soils.For the thickness,location and angle of the weak strata,the variation in the support pressure is given in this paper.To more intuitively depict the change in the failure mechanism in the presence of weak strata,the change in the failure mechanism under different thicknesses and weaknesses of weak strata is plotted.