特征点自动标定的颅面复原及其评估方法

为了采用计算机技术从人头颅骨样本重构出个性化的三维表面面部特征,提出一种特征点自动标定的颅面复原算法.首先利用特征点自动标定算法对待复原颅骨模型进行特征点标定;然后在基于模板变形的颅面复原算法基础上引入Laplace坐标网格变形技术,以实现待复原颅骨模型的颅面复原.为了验证文中算法进行颅面复原结果的可靠性,提出一种采用计算颅面整体特征和局部特征相似度的颅面复原结果评估方法.实验结果表明,文中提出的特征点自动标定算法大大提高了颅面复原前期工作的效率,颅面复原算法对待复原颅骨的颅面复原取得了良好的复原效果;同时,颅面复原结果评估方法达到了主观与客观评价上的一致,对复原结果验证有良好的指导作用.     

基于多不动点约束的网格模型局部编辑

传统的自由变形方法通过计算控制晶格来变形,不适用于精确变形的情况。针对此问题,提出一种基于多不动点约束的网格模型局部编辑算法,该算法通过多个不动点的合理配置设定多种复杂的约束条件,实现网格模型的局部编辑,进而精确的变形模型。实验表明算法计算代价低,可实现精确变形。     

利用Principal Warps评估颅面几何相似度

针对目前颅面相似度评估主要依靠主观验证、缺乏衡量相似度的物理量等问题,提出一种3维颅面几何相似度评估方法。将颅面相似度评估看做是待比较颅面到数据库中其余颅面的弯曲变形,计算出待比较颅面的Principal Warps作为新的基,给出颅面间对应全局特征点的选择方法,并利用薄板样条函数建立映射,从而计算出相应的弯曲变形矩阵,将该矩阵表示为基与系数矩阵的乘积。实现了在待比较颅面固定的情况下,用系数矩阵来衡量颅面间的变形程度,并在此基础上定义了颅面间几何相似度距离,给出了具体比较方法。实验结果验证了该方法的有效性。     

生理点配准的颅面局部形态关系建模

为提高对颅骨与面皮之间形态关系建模的准确度,提出一种生理点配准的颅面局部形态关系建模方法。以特征点对应关系为约束条件,基于TPS变形实现颅面初配准;根据欧氏距离与局部几何特征的加权距离确定顶点的最优生理对应关系,建立分类颅面模型库;将颅面形态关系建模问题分解为对每一面皮生理点各坐标分量建模的子问题集,运用单因变量多自变量PLSR,以面皮生理点的各坐标分量为因变量,选取显著相关的颅骨生理点相应坐标分量为自变量,建立由各面皮生理点坐标计算模型构成的局部形态关系模型。实验结果表明该方法可更准确有效地描述颅面形态变化关系。     

基于参数化的三维颅面配准

针对颅面配准问题,提出通过对颅面进行参数化将其转换成二维参数域的对应问题。首先,根据人类的生理特征标定6个特征点,利用这些特征点将颅面转换到一个统一的坐标系以实现姿态和大小的统一;其次,以两个外眼角为约束对参考颅面进行最小二乘保角映射,计算出6个特征点的参数值;然后,以这六个生理特征点的参数值为约束,利用最小二乘保角映射将任一待配准模型映射到二维参数域;最后,根据二维参数域确定三维颅面上的对应点,从而实现三维数据配准。为了验证所提方法,以对应点为控制点,利用薄板样条(TPS)变换把参考颅面变形到目标颅面,以变形后两个模型上对应点之间的几何距离的平均为度量,将所提算法和基于主轴分析的迭代最近点(ICP)配准以及基于随机采样控制点的迭代TPS配准方法进行了比较,实验结果表明,所提算法的配准效果优于其他两种方法。     

基于切平面中值坐标的Laplacian网格变形算法

网格模型变形往往需要保持局部几何细节,Laplacian网格变形算法能够较好地保持局部几何细节特征,但细节特征描述子-Laplacian坐标的计算欠缺精确性.从平面多边形中值坐标的角度出发,对Laplacian坐标进行重新定义,将顶点的一阶邻域投影到顶点处切平面上,根据顶点相对投影点的中值坐标构建的Laplacian坐标能够精确地描述模型的局部几何细节特征,实验验证能够获得较好的编辑效果.     

基于层次B样条的网格模型变形技术

针对常用的网格模型提出了一个基于层次B样条控制的三维网格空间变形框架．首先由用户交互地选取编辑区域,由程序完成编辑区域的参数化和均匀重采样;然后用层次B样条光顺拟合这些均匀采样点,所得的R样条曲面作为网格模型的基曲面,计算待编辑区域中网格顶点相对该B样条基曲面的局部坐标,该局部坐标平移、旋转不变,可视为模型的内蕴几何特征,并作为变形操作中的不变量．用户通过编辑层次B样条基曲面或者直接编辑三维网格模型,可实现多分辨率变形．实验结果表明：该方法操作直观方便,无论对整体还是局部变形,都能取得可控、可靠的变形效果,且采刚B样条曲面的控制手段易于与已有的造型系统合成．     

基于TPS变形的3D面皮层次点对应方法

在统计模型的颅面复原中,针对如何建立三维面皮间顶点的生理一致对应关系的问题,提出一种面皮层次点对应方法(HPCM).根据Frankfurt坐标系下特征点的严格对应关系对样本面皮进行薄板样条变形,使其与模板面皮近似重合.在此基础上分别建立体素模型,结合顶点的欧式距离、局部相对位置与几何特征等多重约束确定最优对应点.实验结果表明,HPCM提高了点对应的精度,可有效建立颅面统计复原所需的具备生理点对应关系的面皮样本.     

融合空间结构特征的三维模型局部检索方法

针对局部信息识别的重要性,在骨架提取的基础上,提出了一种新的三维模型局部检索方法。该算法在基于骨架树进行图结构匹配的初步筛选后,融入空间结构特征和几何细节特征,进行局部相似度的计算。大量实验证明,本方法对于模型的局部匹配有很好的鲁棒性和高效性。     

保持细节的网格曲面局部变形算法

针对直接控制自由变形算法(DFFD)在对大规模网格模型实施局部变形时细节保持性差的问题,以网格曲面上的离散泊松方程和微分算子为理论基础,提出一种完全自动化的网格模型局部变形算法。基本思想是依据用户对模型上控制顶点的移动及网格的表面几何特征,由算法自动判断得到变形区域,继而将用户对控制顶点的编辑操作映射为对变形区域梯度场地操作,最后通过泊松重建得到变形后的网格。优点是在使模型表面的局部几何细节得到保持的基础上省略了人为划定变形区域的步骤。     

Motion estimation of elastic articulated objects from points and contours with volume invariable constraint

This paper presents a model of elastic articulated objects based on revolving conic surface and a method of model-based motion estimation. The model includes 3D object skeleton and deformable surfaces that can represent the deformation of human body surfaces. In each limb, surface deformation is represented by adjusting one or two deformation parameters. Then, the 3D deformation parameters are determined by corresponding 2D image points and contours with volume invariable constraint from a sequence of stereo images. The 3D motion parameters are estimated based on the 3D model. The algorithm presented in this paper includes model-based parameter estimation of motion and parameter determination of deformable surfaces.     

New algorithm for 3D facial model reconstruction and its application in virtual reality

3D human face model reconstruction is essential to the generation of facial animations that is widely used in the field of virtual reality (VR). The main issues of 3D facial model reconstruction based on images by vision technologies are in twofold: one is to select and match the corresponding features of face from two images with minimal interaction and the other is to generate the realistic-looking human face model. In this paper, a new algorithm for realistic-looking face reconstruction is presented based on stereo vision. Firstly, a pattern is printed and attached to a planar surface for camera calibration, and corners generation and corners matching between two images are performed by integrating modified image pyramid Lucas-Kanade (PLK) algorithm and local adjustment algorithm, and then 3D coordinates of corners are obtained by 3D reconstruction. Individual face model is generated by the deformation of general 3D model and interpolation of the features. Finally, realistic-looking human face model     

骨架驱动的三维模型变形方法

为发展三维网格模型的变形技术,研究了多种三维模型变形算法,通过对骨架驱动变形算法的深入研究,针对现行算法多是以单一骨架驱动变形的不足,提出了一种新的基于多骨架点驱动的交互式局部变形方法.有效结合模型的骨架图结构,确定各骨架点对应的局部区域.并将骨架点拟合为二次Bézier曲线,通过交互式拖动任意骨架点计算与之相连的多骨架点的动态变化,实现模型局部区域的自然形变.实验结果表明了该算法的有效性和直观性.     

基于 Kinect 的拉普拉斯网格形变三维人脸建模

为了快速创建真实感较强的三维人脸模型,提出了基于 Kinect 的拉普拉斯网格形 变建模方法。利用 Kinect 获取彩色和深度图像信息,对深度图像进行双边滤波处理,对彩色图 像进行低层级顶点定位;构建标准三维人脸模型,并为该人脸模型中的顶点建立低、中、高 3 个级别的层级结构,通过低、中层级中顶点的位置关系创建 Sibson 局部坐标约束;利用该约束 构建彩色图像中间层级顶点,并结合深度信息对标准三维人脸模型进行拉普拉斯网格变形,获 得真实感较强的三维人脸模型。实验结果表明,该算法在建模的真实感上得到了提高,与对比 算法相比,在建模时间上得到很大的优化。     

Nonrigid structure-from-motion: estimating shape and motion with hierarchical Priors

This paper describes methods for recovering time-varying shape and motion of non-rigid 3D objects from uncalibrated 2D point tracks. For example, given a video recording of a talking person, we would like to estimate the 3D shape of the face at each instant, and learn a model of facial deformation. Time-varying shape is modeled as a rigid transformation combined with a non-rigid deformation. Reconstruction is ill-posed if arbitrary deformations are allowed, and thus additional assumptions about deformations are required. We first suggest restricting shapes to lie within a low-dimensional subspace, and describe estimation algorithms. However, this restriction alone is insufficient to constrain reconstruction. To address these problems, we propose a reconstruction method using a Probabilistic Principal Components Analysis (PPCA) shape model, and an estimation algorithm that simultaneously estimates 3D shape and motion for each instant, learns the PPCA model parameters, and robustly fills-in missing data points. We then extend the model to model temporal dynamics in object shape, allowing the algorithm to robustly handle severe cases of missing data.     

基于水平集的3D左心室表面重建

提出了基于分层2D MRI图像重建3D左心室表面的算法．分层2D MRI图像能够跟踪左心室边界在成像平面内的变形,但由于缺少层问数据,层间边界形变的信息难以获取．为了重建左心室的形状,使用基于形变模型的方法：首先建立变形曲面的动力学方程;再将成像坐标系中的图像平面映射到重建坐标系,根据图像数据构造外力,使用平均曲率构造变形曲面的弹性力,然后用水平集数值解法求解动力学方程以重建左心室的表面．实验结果证明了算法的有效性．     

RAS: A Data-Driven Rigidity-Aware Skinning Model For 3D Facial Animation

We present a novel data-driven skinning model—rigidity-aware skinning (RAS) model, for simulating both active and passive 3D facial animation of different identities in real time. Our model builds upon a linear blend skinning (LBS) scheme, where the bone set and skinning weights are shared for diverse identities and learned from the data via a sparse and localized skinning decomposition algorithm. Our model characterizes the animated face into the active expression and the passive deformation: The former is represented by an LBS-based multi-linear model learned from the FaceWareHouse data set, and the latter is represented by a spatially varying as-rigid-as-possible deformation applied to the LBS-based multi-linear model, whose rigidity parameters are learned from the data by a novel rigidity estimation algorithm. Our RAS model is not only generic and expressive for faithfully modelling medium-scale facial deformation, but also compact and lightweight for generating vivid facial animation in real time. We validate the efficiency and effectiveness of our RAS model for real-time 3D facial animation and expression editing.     

Topology based 2D engineering drawing and 3D model matching for process plant

Process plant models mainly include 3D models and 2D engineering drawings. Matching calculation between these CAD models has wide applicability in model consistency check and retrieval. In process plant, engineering design standards make 2D engineering drawing and 3D model differ in geometry, proportion and structure, leading to the inapplicability of current shape-feature based matching approaches. Since connection relationships between components are the core of a process plant, a topology based algorithm is proposed. Firstly, by exploiting components as vertices and relationships as edges, both 2D engineering drawing and 3D model are preprocessed into graph structures. Then each model’s relationship types are extracted from the graph. Finally, regarding the extracted relationship types as primary feature, feature similarity is calculated to measure the matching degree between their corresponding models. The proposed algorithm is geometric deformation invariant. Experiments with industrial applications are presented, which demonstrates the effectiveness and feasibility of the proposed algorithm.     

基于形变模型的多角度三维人脸实时重建

摘 要：采用人脸特征点调整三维形变模型的方法应用于面部三维重建,但模型形变的计 算往往会产生误差,且耗时较长。因此运用人脸二维特征点对通用三维形变模型的拟合方法进 行改进,提出了一种视频流的多角度实时三维人脸重建方法。首先利用带有三层卷积网络的 CLNF 算法识别二维特征点,并跟踪特征点位置;然后由五官特征点位置估计头部姿态,更新 模型的表情系数,其结果再作用于 PCA 形状系数,促使当前三维模型发生形变;最后采用 ISOMAP 算法提取网格纹理信息,进行纹理融合形成特定人脸模型。实验结果表明,该方法在 人脸重建过程中具有更好的实时性能,且精确度有所提高。     

基于特征点的三维人脸形变模型

针对传统三维人脸形变模型效率低的不足,提出了一个基于特征点的线性人脸形变模型.首先,提出一种基于平面模板的对应方法,自动地实现了三维人脸的稠密点对应,建立了人脸线性模型.然后,提出一个基于动态成分的线性形变模型,选择与目标人脸最相关的主成分作为形变模型的基空间.最后,采用一个全局与局部双重形变框架来完成人脸形状建模.实验结果表明,该方法能够获得较好的建模精度,可以通过真实照片上的少量特征点生成逼真的三维人脸模型.