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.

High Efficiency Crypto-Watermarking System Based on Clifford-Multiwavelet for 3D Meshes Security

Since 3D mesh security has become intellectual property,3D watermarking algorithms have continued to appear to secure 3D meshes shared by remote users and saved in distant multimedia databases.The novelty of our approach is that it uses a new Clifford-multiwavelet transform to insert copyright data in a multiresolution domain,allowing us to greatly expand the size of the watermark.After that,our method does two rounds of insertion,each applying a different type of Clifford-wavelet transform.Before being placed into the Clifford-multiwavelet coefficients,the watermark,which is a mixture of the mesh description,source mesh signature(produced using SHA512),and a logo encrypted using the RSA(Ronald Shamir Adleman)technique,is encoded using Turbo-code.Using the Least Significant Bit method steps,data embedding involves modulation and insertion processes.Finally,the watermarked mesh is reconstructed using the inverse Cliffordmultiwavelet transform.Due to the utilization of a hybrid insertion domain,our technique has demonstrated a very high insertion rate while retaining mesh quality.The mesh is watermarked,and the extracted data is acquired in real-time.Our approach is also resistant to the most common types of attacks.Our findings reveal that the current approach improves on previous efforts.

基于智能优化的3D mesh微调算法

3D mesh简化是计算机图形学中的关键技术。大多数简化算法旨在权衡被简化3D mesh的占用内存和近似误差,因此很难找到最优的简化3D mesh。为了解决这一问题,文章提出了一种新的3D mesh微调算法。该算法通过调整被简化的3D mesh的点坐标,以搜索具有最小近似误差的简化3D mesh。实验结果表明,设计的微调算法可以进一步减小被简化的3D mesh的近似误差,并缩小被简化3D mesh与原始3D mesh之间的外观差距。

3D网布包覆仪表板乘客侧气囊静态点爆与外观质量的控制措施

3D网布包覆仪表板以其产品轻量化、零件开发周期短、表皮颜色纹理切换自由度高等自身优势,近年来被新能源汽车所青睐,并广泛应用。对这一兴起的新型热压包覆仪表板,进行外观质量的有效控制来满足客户对内饰质量越来越高的需要,便显得尤为重要。

在3D-Mesh网络中的两种路由研究

在研究并行计算机系统容错时,路由算法是一个极为重要的研究课题。主要研究的是自适应路由算法和确定性路由算法在3D-Mesh网络上的性能。在每个结点具有独立的出错概率的模型下,提出的方法使得能够严格地推导出路由算法的成功概率,从而能够对算法进行分析和比较。研究结果表明,自适应路由算法具有明显的优势。一方面,自适应路由算法基于局部信息而变得高效;另一方面,自适应路由算法对于结点出错和网络规模具有更好的健壮性,而使其具有更高的成功概率。

Fast ion diffusion alloy layer facilitating 3D mesh substrate for dendrite-free zinc-ion hybrid capacitors

Although aqueous zinc ion hybrid capacitors have advantageous integration of batteries and supercapacitors,they still suffer from the inherent problems of dendrite growth and interfacial side reactions on Zn anodes.Herein,a universal fast zinc-ion diffusion layer on a three-dimensional(3 D)mesh structure model is demonstrated to effectively improve Zn plating/stripping reversibility.The fast ion diffusion alloy layer accelerates the Zn^(2+)migration in an orderly manner to homogenize Zn^(2+)flux and overcomes the defects of the commercial mesh substrate,effectively avoiding dendrite growth and side reactions.Consequently,the proof-of-concept silver-zinc alloy modified stainless steel mesh delivers superb reversibility with the high coulombic efficiency over 99.4%at 4 mA cm^(-2)after 1600 cycles and excellent reliability of over 830 h at 1 mA cm^(-2),Its feasibility is also evidenced in commercial zinc ion hybrid capacitors with activated carbon as the cathode.This work enriches the fundamental comprehension of fast zinc-ion diffusion layer combined with a 3 D substrate on the Zn deposition and opens a universal approach to design advanced host for Zn electrodes in zinc ion hybrid capacitors.

Securing 3D Point and Mesh Fog Data Using Novel Chaotic Cat Map

With the rapid evolution of Internet technology,fog computing has taken a major role in managing large amounts of data.The major concerns in this domain are security and privacy.Therefore,attaining a reliable level of confidentiality in the fog computing environment is a pivotal task.Among different types of data stored in the fog,the 3D point and mesh fog data are increasingly popular in recent days,due to the growth of 3D modelling and 3D printing technologies.Hence,in this research,we propose a novel scheme for preserving the privacy of 3D point and mesh fog data.Chaotic Cat mapbased data encryption is a recently trending research area due to its unique properties like pseudo-randomness,deterministic nature,sensitivity to initial conditions,ergodicity,etc.To boost encryption efficiency significantly,in this work,we propose a novel Chaotic Cat map.The sequence generated by this map is used to transform the coordinates of the fog data.The improved range of the proposed map is depicted using bifurcation analysis.The quality of the proposed Chaotic Cat map is also analyzed using metrics like Lyapunov exponent and approximate entropy.We also demonstrate the performance of the proposed encryption framework using attacks like brute-force attack and statistical attack.The experimental results clearly depict that the proposed framework produces the best results compared to the previous works in the literature.

An Eigen-Normal Approach for 3D Mesh Watermarking Using Support Vector Machines

The use of support vector machines （SVM） for watermarking of 3D mesh models is investigated. SVMs have been widely explored for images, audio, and video watermarking but to date the potential of SVMs has not been explored in the 3D watermarking domain. The proposed approach utilizes SVM as a binary classifier for the selection of vertices for watermark embedding. The SVM is trained with feature vectors derived from the angular difference between the eigen normal and surface normals of a 1-ring neighborhood of vertices taken from normalized 3D mesh models. The SVM learns to classify vertices as appropriate or inappropriate candidates for modification in order to accommodate the watermark. Experimental results verify that the proposed algorithm is imperceptible and robust against attacks such as mesh smoothing, cropping and noise addition.

Fragile Watermarking of 3D Models Using Genetic Algorithms

This paper describes a novel algorithm for fragile watermarking of 3D models. Fragile watermarking requires detection of even minute intentional changes to the 3D model along with the location of the change. This poses a challenge since inserting random amount of watermark in all the vertices of the model would generally introduce perceptible distortion. The proposed algorithm overcomes this challenge by using genetic algorithm to modify every vertex location in the model so that there is no perceptible distortion. Various experimental results are used to justify the choice of the genetic algorithm design parameters. Experimental results also indicate that the proposed algorithm can accurately detect location of any mesh modification.

Fully Nonlinear Simulation for Fluid/Structure Impact：A Review

This paper presents a review of the work on fluid/structure impact based on inviscid and imcompressible liquid and irrotational flow. The focus is on the velocity potential theory together with boundary element method （BEM）. Fully nonlinear boundary conditions are imposed on the unknown free surface and the wetted surface of the moving body. The review includes （1） vertical and oblique water entry of a body at constant or a prescribed varying speed, as well as free fall motion, （2） liquid droplets or column impact as well as wave impact on a body, （3） similarity solution of an expanding body. It covers two dimensional （2D）, axisymmetric and three dimensional （3D） cases. Key techniques used in the numerical simulation are outlined, including mesh generation on the multivalued free surface, the stretched coordinate system for expanding domain, the auxiliary function method for decoupling the mutual dependence of the pressure and the body motion, and treatment for the jet or the thin liquid film developed during impact.

一种面向三维众核微处理器的新型NoC拓扑结构

三维微处理器具有集成度高、全局互连线短及连接部件多的优势,但是传统的三维拓扑结构在大规模系统中无法充分利用垂直方向上低延时高带宽的特性,很难满足大规模众核微处理器低直径、高带宽、高扩展性的需求。针对三维NoC网络直径大、可扩展性要求高以及路由端口多的问题,提出了一种基于多级垂直域的三维拓扑结构—V-Spidergon,其在水平层上采用Spidergon结构,在垂直方向上采用多级垂直域扩展结构,域内及域间均实现全互连。实验数据表明,在8层、16层和32层堆叠下,V-Spidergon结构的延时较3D-Mesh分别降低15.1%、28.5%和55.7%,较NoC-Bus分别降低11.5%、32.7%和77.6%;在15%和100%负载率注入情形下,V-Spidergon的平均延时表现出与水平层数增加不相关的特性。

A new diagnosis strategy under the PMC model and applications

A new diagnosis method, called Double-Syndrome diagnostic, is proposed, which can identify faulty nodes by comparing 2 different syndromes. For the same system, the average number of faulty nodes identified correctly by the Double-Syndrome diagnostic is much greater than the t-diagnosability and the(t_1/t_1)-diagnosability of the system. Furthermore, in order to identify the remaining faulty nodes in the system, two strategies of fault diagnostic are proposed, one is called(k, t)-fault diagnosable strategy, another is called(k, t/t)-fault diagnosable strategy. Besides, the conditional(k, t)-diagnosable((k, t/t)-diagnosable) system is introduced. Furthermore, the conditional diagnosabilities are proved for some regular(k, t)-diagnosable and(k, t/t)-diagnosable networks such as n-dimensional hypercube network and n-dimensional star network. And then, for a system, its(k,t)-conditional diagnosability and its(k, t/t)-conditional diagnosability are identical, and in the worst case, they are equal to their traditional conditional diagnosability.

Research on two-step throttle characteristics of double-rotation valve port for hydraulic servo joint

The hydraulic robot with large output torque is widely used in industry,however,its precision is not high.In order to solve this problem,this paper presents a new structure of rotary valve with double-rotation valve port,which can improve the two-step throttle characteristics of the valve port,reduce the cavitation phenomenon of the valve port,and increase the output accuracy of the hydraulic servo joint.Firstly,the internal flow field of the rotary valve is simulated by using the sliding grid technology of FLUENT software,and the changing rule of the throttle position in the working process of the structure is analyzed.Secondly,compared with the simulation results of rotary valve with single-rotation valve port,it is shown that the two-step throttle characteristics of the structure are less affected by the change of the opening of the rotary valve,and the cavitation index of the joint valve port is reduced.Finally,the influence of the rotation speed of the valve core,oil supply pressure and key dimension of valve core on throttle characteristics of rotary valve have been analyzed.

3D hand pose and shape estimation from monocular RGB via efficient 2D cues

Estimating 3D hand shape from a single-view RGB image is important for many applications.However,the diversity of hand shapes and postures,depth ambiguity,and occlusion may result in pose errors and noisy hand meshes.Making full use of 2D cues such as 2D pose can effectively improve the quality of 3D human hand shape estimation.In this paper,we use 2D joint heatmaps to obtain spatial details for robust pose estimation.We also introduce a depth-independent 2D mesh to avoid depth ambiguity in mesh regression for efficient hand-image alignment.Our method has four cascaded stages:2D cue extraction,pose feature encoding,initial reconstruction,and reconstruction refinement.Specifically,we first encode the image to determine semantic features during 2D cue extraction;this is also used to predict hand joints and for segmentation.Then,during the pose feature encoding stage,we use a hand joints encoder to learn spatial information from the joint heatmaps.Next,a coarse 3D hand mesh and 2D mesh are obtained in the initial reconstruction step;a mesh squeeze-and-excitation block is used to fuse different hand features to enhance perception of 3D hand structures.Finally,a global mesh refinement stage learns non-local relations between vertices of the hand mesh from the predicted 2D mesh,to predict an offset hand mesh to fine-tune the reconstruction results.Quantitative and qualitative results on the FreiHAND benchmark dataset demonstrate that our approach achieves state-of-the-art performance.

Evaluation for Small Visual Difference Between Conforming Meshes on Strain Field

This paper gives a method of quantifying small visual differences between 3D mesh models with conforming topology, based on the theory of strain fields. Strain field is a geometric quantity in elasticity which is used to describe the deformation of elastomer. In this paper we consider the 3D models as objects with elasticity. The further demonstrations are provided： the first is intended to give the reader a visual impression of how our measure works in practice; and the second is to give readers a visual impression of how our measure works in evaluating filter algorithms. Our experiments show that our difference estimates are well correlated with human perception of differences. This work has applications in the evaluation of 3D mesh watermarking, 3D mesh compression reconstruction, and 3D mesh filtering.

Deep 3D mesh watermarking with self-adaptive robustness

Robust 3D mesh watermarking is a traditional research topic in computer graphics,which provides an efficient solution to the copyright protection for 3D meshes.Traditionally,researchers need manually design watermarking algorithms to achieve suffcient robustness for the actual application scenarios.In this paper,we propose the first deep learning-based 3D mesh watermarking network,which can provide a more general framework for this problem.In detail,we propose an end-to-end network,consisting of a watermark embedding sub-network,a watermark extracting sub-network and attack layers.We employ the topology-agnostic graph convolutional network(GCN)as the basic convolution operation,therefore our network is not limited by registered meshes(which share a fixed topology).For the specific application scenario,we can integrate the corresponding attack layers to guarantee adaptive robustness against possible attacks.To ensure the visual quality of watermarked 3D meshes,we design the curvature consistency loss function to constrain the local geometry smoothness of watermarked meshes.Experimental results show that the proposed method can achieve more universal robustness while guaranteeing comparable visual quality.

Approximating interior bounded box of 3D character mesh model based on its skeleton and symmetry

Purpose – In the process of robot shell design, it is necessary to match the shape of the input 3D originalcharacter mesh model and robot endoskeleton, in order to make the input model fit for robot and avoidcollision. So, the purpose of this paper is to find an object of reference, which can be used for the process ofshape matching.Design/methodology/approach – In this work, the authors propose an interior bounded box (IBB)approach that derives from oriented bounding box (OBB). This kind of box is inside the closed mesh model.At the same time, it has maximum volume which is aligned with the object axis but is enclosed by all the meshvertices. Based on the IBB of input mesh model and the OBB of robot endoskeleton, the authors can completethe process of shape matching. In this paper, the authors use an evolutionary algorithm, covariance matrixadaptation evolution strategy (CMA-ES), to approximate the IBB based on skeleton and symmetry of inputcharacter mesh model.Findings – Based on the evolutionary algorithm CMA-ES, the optimal position and scale informationof IBB can be found. The authors can obtain satisfactory IBB result after this optimization process.The output IBB has maximum volume and is enveloped by the input character mesh model as well.Originality/value – To the best knowledge of the authors, the IBB is first proposed and used in the field ofrobot shell design. Taking advantage of the IBB, people can quickly obtain a shell model that fit for robot.At the same time, it can avoid collision between shell model and the robot endoskeleton.

3D Face Reconstruction Using Images from Cameras with Varying Parameters

In this paper, we present a new technique of 3D face reconstruction from a sequence of images taken with cameras having varying parameters without the need to grid. This method is based on the estimation of the projection matrices of the cameras from a symmetry property which characterizes the face, these projections matrices are used with points matching in each pair of images to determine the 3D points cloud, subsequently, 3D mesh of the face is constructed with 3D Crust algorithm. Lastly, the 2D image is projected on the 3D model to generate the texture mapping. The strong point of the proposed approach is to minimize the constraints of the calibration system： we calibrated the cameras from a symmetry property which characterizes the face, this property gives us the opportunity to know some points of 3D face in a specific well-chosen global reference, to formulate a system of linear and nonlinear equations according to these 3D points, their projection in the image plan and the elements of the projections matrix. Then to solve these equations, we use a genetic algorithm which consists of finding the global optimum without the need of the initial estimation and allows to avoid the local minima of the formulated cost function. Our study is conducted on real data to demonstrate the validity and the performance of the proposed approach in terms of robustness, simplicity, stability and convergence.

Three-dimensional deformation in curl vector field

Deformation is an important research topic in graphics.There are two key issues in mesh deformation:(1) selfintersection and(2) volume preserving.In this paper,we present a new method to construct a vector field for volume-preserving mesh deformation of free-form objects.Volume-preserving is an inherent feature of a curl vector field.Since the field lines of the curl vector field will never intersect with each other,a mesh deformed under a curl vector field can avoid self-intersection between field lines.Designing the vector field based on curl is useful in preserving graphic features and preventing self-intersection.Our proposed algorithm introduces distance field into vector field construction;as a result,the shape of the curl vector field is closely related to the object shape.We define the construction of the curl vector field for translation and rotation and provide some special effects such as twisting and bending.Taking into account the information of the object,this approach can provide easy and intuitive construction for free-form objects.Experimental results show that the approach works effectively in real-time animation.