基于多角度照片的真实感三维人脸建模的研究

为了提高重构的三维人脸的真实感,提出了以Candide-3模型作为通用的人脸模型的一种改进的利用多角度照片进行合成的方法。首先利用改进的双目立体视觉系统,将获取的二维信息映射到三维空间上,测定特征点的深度信息;然后采用自动和交互的方式对Candide-3模型进行校准,合成三维人脸模型。最后采用改进的多角度映射方法对皮肤纹理进行映射贴图,合成具有真实感的三维人脸模型。验证表明,该方法能够更好的生成一个具有较好逼真度的真实感的三维人脸模型。     

Realistic face modeling based on multiple deformations

On the basis of the assumption that the human face belongs to a linear class, a multiple-deformation model is proposed to recover face shape from a few points on a single 2D image. Compared to the conventional methods, this study has the following advantages. First, the proposed modified 3D sparse deforming model is a noniterative approach that can compute global translation efficiently and accurately. Subsequently, the overfitting problem can be alleviated based on the proposed multiple deformation model. Finally, by keeping the main features, the texture generated is realistic. The comparison results show that this novel method outperforms the existing methods by using ground truth data and that realistic 3D faces can be recovered efficiently from a single photograph.     

基于多帧二维动画图像的三维自动生成技术

针对传统的三维自动生成方法存在效果差的问题,提出基于对象层次与表面层次随动渲染技术的多帧二维动画图像三维自动生成技术。采用相似度度量方法进行图形渲染的表面层次平滑处理,利用对象层次与表面层次随动信息融合方法进行动画图像渲染,实现多帧二维动画图像的三维重构与动态生成。仿真结果表明,采用改进方法进行多帧二维动画图像重构生成,图像具有较高的逼真性。     

Automatic face cloning and animation using real-time facial featuretracking and speech acquisition

We describe the components of the system used for real-time facial communication using a cloned head. We begin with describing the automatic face cloning using two orthogonal photographs of a person. The steps in this process are the face model matching and texture generation. After an introduction to the MPEG-4 parameters that we are using, we proceed with the explanation of the facial feature tracking using a video camera. The technique requires an initialization step and is further divided into mouth and eye tracking. These steps are explained in detail. We then explain the speech processing techniques used for real-time phoneme extraction and subsequent speech animation module. We conclude with the results and comments on the integration of the modules towards a complete system     

Research on a face recognition algorithm based on 3D face data and 2D face image matching

Under the condition of weak light or no light, the recognition accuracy of the mature 2D face recognition technology decreases sharply. In this paper, a face recognition algorithm based on the matching of 3D face data and 2D face images is proposed. Firstly, 3D face data is reconstructed from the 2D face in the database based on the 3DMM algorithm, and the face depth image is obtained through orthogonal projection. Then, the average curvature map of the face depth image is used to enhance the data of the depth image. Finally, an improved residual neural network based on the depth image and curvature is designed to compare the scanned face with the face in the database. The method proposed in this paper is tested on the 3D face data in three public face datasets (Texas 3DFRD, FRGC v2.0, and Lock3DFace), and the recognition accuracy is 84.25%, 83.39%, and 78.24%, respectively.     

Multi-pose 3D face recognition based on 2D sparse representation

The increasing availability of 3D facial data offers the potential to overcome the difficulties inherent with 2D face recognition, including the sensitivity to illumination conditions and head pose variations. In spite of their rapid development, many 3D face recognition algorithms in the literature still suffer from the intrinsic complexity in representing and processing 3D facial data. In this paper, we propose the intrinsic 3D facial sparse representation (I3DFSR) algorithm for multi-pose 3D face recognition. In this algorithm, each 3D facial surface is first mapped homeomorphically onto a 2D lattice, where the value at each site is the depth of the corresponding vertex on the 3D surface. Each 2D lattice is then interpolated and converted into a 2D facial attribute image. Next, the sparse representation is applied to those attribute images. Finally, the identity of each query face can be obtained by using the corresponding sparse coefficients. The innovation of our approach lies in the strategy of converting irregular 3D facial surfaces into regular 2D attribute images such that 3D face recognition problem can be solved by using the sparse representation of those attribute images. We compare the proposed algorithm to three widely used 3D face recognition algorithms in the GavabDB database, to six state-of-the-art algorithms in the FRGC2.0 database, and to three baseline algorithms in the NPU3D database. Our results show that the proposed I3DFSR algorithm can substantially improve the accuracy and efficiency of multi-pose 3D face recognition.     

基于虚拟现实技术的3D动画场景平面设计

针对当前方法难以获取3D动画场景完整正确的信息,存在计算复杂、三维动画场景连续性较差的问题,提出基于虚拟现实技术的3D动画场景平面设计方法。该方法先在空间中建立代表动画场景深度信息的网格节点,将摄像机坐标系与世界坐标系的坐标进行变换,得到关于动画场景图像候选网格节点的深度坐标值;利用动画场景的深度图像进行预处理以平滑噪声,获取动画场景图像的三维点云;根据动画场景图像特征点与三维点云之间的关系得到动画场景图像的三维特征点,利用ICP法完成动画场景图像点云的精确配准,由此建立3D动画场景模型。实验结果表明,所提方法能够有效提升3D动画场景的重建精度,且具有较强的实时性及稳定性。     

基于深度卷积网络的3D人脸重构算法

基于单张人脸图片的3D人脸模型重构,无论是在计算机图形领域还是可见光成像领域都是一个极具挑战性的研究方向,对于人脸识别、人脸成像、人脸动画等实际应用更是具有重要意义。针对目前算法复杂度较高、运算量较大且存在局部最优解和初始化不良等问题,本文提出了一种基于深度卷积神经网络的单张图片向3D人脸自动重构算法。该算法首先基于3D转换模型来提取2D人脸图像的密集信息,然后构建深度卷积神经网络架构、设计总体损失函数,直接学习2D人脸图像从像素到3D坐标的映射,从而实现了3D人脸模型的自动构建。算法对比与仿真实验表明,该算法在3D人脸重建上的归一化平均误差更低,且仅需一张2D人脸图像便可自动重构生成3D人脸模型。所生成的3D人脸模型鲁棒性好,重构准确,完整保留表情细节,并且对不同姿态的人脸也具有较好的重建效果,能够在三维空间中无死角自由呈现,将满足更多实际应用需求。     

3D facial model reconstruction, expressions synthesis and animation using single frontal face image

With better understanding of face anatomy and technical advances in computer graphics, 3D face synthesis has become one of the most active research fields for many human-machine applications, ranging from immersive telecommunication to the video games industry. In this paper we proposed a method that automatically extracts features like eyes, mouth, eyebrows and nose from the given frontal face image. Then a generic 3D face model is superimposed onto the face in accordance with the extracted facial features in order to fit the input face image by transforming the vertex topology of the generic face model. The 3D-specific face can finally be synthesized by texturing the individualized face model. Once the model is ready six basic facial expressions are generated with the help of MPEG-4 facial animation parameters. To generate transitions between these facial expressions we use 3D shape morphing between the corresponding face models and blend the corresponding textures. Novelty of our method is automatic generation of 3D model and synthesis face with different expressions from frontal neutral face image. Our method has the advantage that it is fully automatic, robust, fast and can generate various views of face by rotation of 3D model. It can be used in a variety of applications for which the accuracy of depth is not critical such as games, avatars, face recognition. We have tested and evaluated our system using standard database namely, BU-3DFE.     

基于三维扫描的激光演示动画多通道拼接方法

常规激光演示动画多通道拼接方法,演示设备投射图形畸变量较大,导致通道重叠区域至显示区域色彩衰减率较高。针对这一问题,研究基于三维扫描的激光演示动画多通道拼接方法。三维激光扫描动画图形,利用激光发射器,投射三维图形至演示幕布,计算激光发射器内参矩阵,二次曲线近似拟合图形畸变量,几何校正投射图形,百分比量混合三原色输入通道,校正投射图形颜色区域,通过融合函数赋值蒙板像素值,融合蒙板和多通道投射图形,实现无缝拼接。设置对比实验,结果表明,设计方法相比常规方法,针对重叠区域中心点至显示区域中心点演示区域,降低了亮度、对比度、饱和的衰减率,保证了激光演示动画整体色彩一致性。     

基于特征点预测的三维表情人脸合成

对于三维人脸表情合成,基于设备的方法成本高、灵活度低,表情的重建依赖人脸扫描过程中原始人脸表情;基于图像的方法大部分以面部行为编码系统(FACS)为基础,存在FACS兼容性较好的部分模型表现粗糙问题、合成真实度较低等问题.针对于此,本文提出一种基于特征点预测的三维表情合成方法.在三维人脸重建效果较好的3DMM算法基础上...     

Motion-compensated compression of 3D animation models

A new algorithm is proposed to compress animated 3D mesh models. First, an input mesh model is partitioned into segments, and each segment is motion compensated from that of the previous time instance. Then, the motion residuals are effectively compressed by using a transform coding method. It is shown that the proposed algorithm yields a much higher compression ratio than the MPEG-4 codec     

基于虚拟现实的三维动画图像多屏显示系统设计

为解决传统多屏显示系统图像接收速率过低、单路图像输出速率受限等问题,设计基于虚拟现实技术的新型三维动画图像多屏显示系统。利用动画图像处理平台、规划显示电源、三维多屏SOC显示模块的连接方式,完成新型显示系统的硬件运行环境搭建。将虚拟现实技术分割后的三维动画图像作为读取依据,对显示滤波参数进行重新设置,完成新型显示系统的软件运行环境搭建,结合软、硬件运行单元实现基于虚拟现实技术三维动画图像多屏显示系统的搭建。对比实验结果表明,与传统多屏显示系统相比,应用基于虚拟现实技术的新型三维动画图像多屏显示系统后,平均图像接收速率可以达到2.5 MB/s,单路图像输出速率最大值接近120 MB/s。     

一种多特征相结合的三维人脸关键点检测方法

关键点检测是三维人脸识别过程中非常重要的一步,为了提高关键点检测的准确度,提出了一种多特征相结合的三维人脸关键点检测方法。首先对训练集中的三维人脸手工标记关键点,计算三维人脸上每一点的不同特征值,得到每类关键点关于每个特征的均值和方差,其次对关键点和非关键点上的特征进行线性判别分析,得到与每个关键点相关的分值加权向量,将前面得到的均值,方差以及分值加权向量作为线下训练的结果输出。最后对于一个输入模型,结合线下训练的结果得到每个关键点的候选点,利用这些候选点构建人脸结构模型。再根据绝对距离约束,相对位置约束,FLM模型一致性分类,自旋图描述符等方法确定最终的关键点。实验部分,从CASIA-3DFaceV1和FRGC V2.0数据库中选不同姿态,不同表情,姿态与表情混合的三个数据集,对其进行关键点检测。实验结果表明,不同姿态的检测率为94.5%,不同表情的检测率为94%,和其他文献相比,检测率平均提高了20%,并且有着较高的运算效率。     

视觉传达设计系统的三维动画优化技术研究

针对当前三维动画优化技术存在一定的不足,如渲染效果不明显等,为了获得更加理想的三维动画优化效果,提出一种视觉传达设计系统的三维动画优化技术.首先,对三维动画优化技术的研究现状进行分析,找到引起三维动画优化效果不佳的原因;然后,采用三维动画图像序列,根据关键帧处图像序列生成深度判断模型,通过对偶原理优化动画图像深度模型;...     

三维人脸建模技术分析及应用

三维人脸建模是计算机视觉和计算机图形学领域中一个研究热点,笔者首先分析了三维人脸建模技术背景意义和研究现状;其次论证了各种三维人脸建模技术的优缺点;最后对三维人脸建模技术的应用领域进行了详细介绍并进一步展望了今后三维人脸建模方向。     

3D MAX动画中材质参数的数字水印算法

为了保护在线多媒体数字资源的版权,提出一种针对3D MAX三维动画的数字水印方案。选定动画中的材质参数作为水印嵌入位置,首先将若干有效材质参数组成一个矩阵,对此矩阵进行小波变换,得到逼近分量和细节分量,其次将水印信息进行PCA分解,然后将小波变换后得到的逼近分量与PCA分解得到的第一分量进行数据融合,最后用融合得到的逼近分量与原始细节分量进行小波逆变换,从而将水印嵌入到材质参数矩阵中,用新矩阵中的元素来重新设置材质,得到嵌入水印的三维动画。实验结果表明,算法简单易行,水印隐蔽性好,抗攻击性能强且扩展性好。     

Adult-child 3D backward face aging model (3D B-FAM)

Face aging has been widely considered in many studies regarding all the potential applications. However, the de-aging known as the rejuvenation or backward modeling has recently received more attention. Previous studies mainly focused on rejuvenating faces from aged adults into young adults using two-dimensional (2D) models. In this work, we propose an extension of a previous 2D adult-child B-FAM into 3D model. This model allows a digital face appearance rejuvenation within a range of [75–3] years old. To evaluate the performances of the proposed approach, first, we proposed two performance evaluation modes, namely: Generic Perception Based and Biometric Verification Mode. Then, the performances have been evaluated over our own 3D database, called Face Time-Machine database constructed using 75 females and 70 males, leading to 500 textured surface meshes. Finally, results show that they are perceptually satisfying and system performance increases by using the faces obtained from our model.     

基于二维图像表示的人脸识别算法研究

尽管传统的人脸识别技术已经有了非常大的进步,在很多方面仍然存在一定的缺陷。文章对二维图像进行了深层次的分析,从二维图像的特征、研究意义以及应用范围进行讨论,再结合人脸识别技术和算法从4个不同的角度切入,对二维图形表示的人脸识别算法进行了详细阐述。