改进的基于特征点软组织厚度的颅面复原方法

现有三维颅面复原技术大多依据颅骨特征点的软组织厚度统计值。针对现有统计值指标涵盖的年龄、胖瘦等属性段较宽泛导致复原面貌缺乏个性的缺点,提出了一种改进方法。首先通过CT扫描仪获得颅面样本数据,并通过图像重构获得三维颅骨和人脸模型;然后采用一种半自动特征点标定方法对三维颅骨样本进行特征点标定,并求解特征点软组织厚度;之后采用支持向量回归方法构建特征点软组织厚度与属性之间的函数关系;最后根据待复原颅骨的属性以及回归函数计算特征点软组织厚度,在此基础上采用薄板样条函数对参考人脸模型进行变形获得复原面貌。实验结果表明,相比于已有方法,该方法能获得更准确的软组织厚度,提高颅面复原的准确度。     

基于偏最小二乘回归局部形状关系建模的颅面复原方法

针对基于主成分分析(PCA)的颅面联合统计复原中建模方法未充分考虑颅骨对面皮表面形状影响的局部性、模型对颅骨与面皮之间形状变化关系描述能力不足的问题,提出一种基于偏最小二乘回归(PLSR)局部形状关系建模的颅面复原方法。首先,深入分析基于PCA的颅面整体形状统计建模方法的缺陷,以及利用PLSR进行局部形状关系统计建模的优势;然后,将PLSR引入到颅面形状关系建模过程中,以按照法医人类学知识分类和具有生理点对应关系的颅面三维表面模型为训练集,针对每一类面皮上的每一个表面顶点,建立关于与其局部紧密相关的颅骨表面顶点集的PLSR坐标计算模型;进而,利用面皮表面顶点的坐标计算模型获得待复原面皮各顶点坐标来实现面貌复原,并给出基于PLSR局部形状关系建模的颅面复原方法的具体步骤;最后,给出通过PLSR局部形状关系建模进行颅面复原的多个实例,并采用有效复原能力和绝对误差等多种评估指标进行对比评估。实验结果表明,基于PLSR局部形状关系建模方法能显著提高颅面复原的准确度。     

基于径向曲线与支持向量回归的颅骨修复方法

颅骨修复技术是对有缺损的颅骨补全对应的缺损部分,进而实现颅骨形状的完整性。针对高维颅骨数据,采用径向曲线来表示颅骨几何特征,结合最小二乘支持向量回归的方法构建颅骨修复模型。提取完整的三维颅骨模型的径向曲线,将其分为已有径向曲线和缺失径向曲线两部分作为训练样本,采用最小二乘支持向量回归统计模型复原出待修复颅骨的缺失径向曲线,进而合并生成待修复颅骨的完整径向曲线,通过迭代最近点算法将合并的颅骨径向曲线与颅骨统计模型进行匹配生成完整的三维颅骨模型。实验结果表明,该方法的平均误差达到6.834×10^-3,比主成分分析方法降低2.90倍,具有更好的修复效果。     

基于等测地区域的三维面貌相似度评价方法

提出一种基于等测地区域的三维面貌相似度评价方法。对待比较的面貌模型,采用鼻尖点重叠以及PCA和ICP配准方法消除平移、旋转因素的影响,根据距离鼻尖点的测地距离,将面貌模型简化为一系列测地区域,利用一个12维的分布向量表征任意2块测地区域之间的空间分布关系,将整个面貌模型中所有等测地区域对应的分布向量组成分布矩阵,计算分布矩阵之间的相似性来衡量2个面貌之间的相似度。实验结果表明,该方法为颅面复原提供了检验平台,是一种有效的表情无关人脸识别方法。     

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.     

颅面复原方法综述

颅面复原是一项依据人的颅骨恢复其对应的面部相貌的研究,在公安法医学、考古学、医学整形等诸多领域有普遍应用,传统手工颅面复原耗费时间长且复原结果难以实现,而近年来逐步兴起的计算机辅助颅面复原方法使得复原结果更加真切、高效。重点归纳和分析计算机辅助颅面复原技术,该复原技术主要基于知识的颅面复原方法和统计模型法,对其中的基于稀疏软组织厚度的颅面复原、基于稠密软组织厚度的颅面复原、统计形变模型和回归模型等重要方法进行详细的阐述,并将各种方法优缺点进行对比,帮助研究人员全面了解颅面复原方法。     

数据配准的颅骨面貌复原方法

颅骨面貌复原技术在法医刑侦领域具有重要应用,为了估计给定颅骨的未知面貌,提出点云配准与五官(鼻、眼睛、嘴)配准结合的颅骨面貌复原框架及基于软组织厚度的评价方法.首先构建颅面数据库并进行坐标校正;然后确定配准点集及其对应关系,采用ICP算法和薄板样条函数两次配准实现参考颅骨与待复原颅骨的精确配准,并将参考模型的软组织厚度...     

三维颅骨模型获取方法研究

颅面复原是一种对人类的颅骨进行面部容貌复原的技术,该技术以人类学、法医学、解剖学中的头骨与面貌相互关系规律为科学依据,广泛应用于考古、刑侦等领域。其中获取三维颅骨模型是实现复原的第一步,颅骨模型的准确与否会直接影响到将来颅面复原的准确性。文中主要介绍了两种获取三维颅骨模型的方法,一种是对cT图像进行面绘制三维重构,另一种是使用三维扫描仪获取三维颅骨模型。之后对获取的颅骨模型建立法兰克福坐标系。实验表明,通过这两种方法获取的颅骨模型为颅面复原提供了良好的颅骨原始数据。     

三维颅骨模型获取方法研究

颅面复原是一种对人类的颅骨进行面部容貌复原的技术,该技术以人类学、法医学、解剖学中的头骨与面貌相互关系规律为科学依据,广泛应用于考古、刑侦等领域。其中获取三维颅骨模型是实现复原的第一步,颅骨模型的准确与否会直接影响到将来颅面复原的准确性。文中主要介绍了两种获取三维颅骨模型的方法,一种是对CT图像进行面绘制三维重构,另一种是使用三维扫描仪获取三维颅骨模型。之后对获取的颅骨模型建立法兰克福坐标系。实验表明,通过这两种方法获取的颅骨模型为颅面复原提供了良好的颅骨原始数据。     

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.     

Craniofacial reconstruction based on multi-linear subspace analysis

Craniofacial reconstruction aims to estimate an individual’s facial appearance from its skull. It can be applied in many multimedia services such as forensic medicine, archaeology, face animation etc. In this paper, a statistical learning based method is proposed for 3D craniofacial reconstruction. In order to well represent the craniofacial shape variation and better utilize the relevance between different local regions, two tensor models are constructed for the skull and the face skin respectively, and multi-linear subspace analysis is used to extract the craniofacial subspace features. A partial least squares regression (PLSR) based mapping from skull subspace to skin subspace is established with the attributes such as age and BMI being considered. For an unknown skull, the 3D face skin is reconstructed using the learned mapping with the help of the skin tensor model. Compared with some other statistical learning based method in literature, the proposed method more directly and properly reflects the shape relationship between the skull and the face. In addition, the proposed method has little manual intervention. Experimental results show that the proposed method is valid.     

基于Candide-3模型的姿态表情人脸识别研究

针对姿态表情严重影响人脸识别准确率的问题,基于Candide-3模型的简化,提出了形状表情关键点拟合的人脸几何结构重建和基于三角网格模型的纹理映射的方法,该方法确定关键特征点,根据人脸的几何结构信息确定姿态角,提取Candide-3模型形状表情对应点,调整模型参数,进行几何结构重建;对几何结构中每个三角网格模型进行纹理影射,得到逼真的特定人脸模型.实验结果表明,该方法提高了人脸重建速度,达到减弱姿态表情对人脸识别影响的目的.     

The Craniofacial Reconstruction from the Local Structural Diversity of Skulls

The craniofacial reconstruction is employed as an initialization of the identification from skulls in forensics. In this paper, we present a two‐level craniofacial reconstruction framework based on the local structural diversity of the skulls. On the low level, the holistic reconstruction is formulated as the superimposition of the selected tissue map on the novel skull. The crux is the accurate map registration, which is implemented as a warping guided by the 2D feature curve patterns. The curve pattern extraction under an energy minimization framework is proposed for the automatic feature labeling on the skull depth map. The feature configuration on the warped tissue map is expected to resemble that on the novel skull. In order to make the reconstructed faces personalized, on the high level, the local facial features are estimated from the skull measurements via a RBF model. The RBF model is learnt from a dataset of the skull and the face feature pairs extracted from the head volume data. The experiments demonstrate the facial outlooks can be reconstructed feasibly and efficiently.     

Passive Three Dimensional Face Recognition Using Iso-Geodesic Contours and Procrustes Analysis

We introduce a new model for personal recognition based on the 3-D geometry of the face. The model is designed for application scenarios where the acquisition conditions constrain the facial position. The 3-D structure of a facial surface is compactly represented by sets of contours (facial contours) extracted around automatically pinpointed nose tip and inner eye corners. The metric used to decide whether a point on the face belongs to a facial contour is its geodesic distance from a given landmark. Iso-geodesic contours are inherently robust to head pose variations, including in-depth rotations of the face. Since these contours are extracted from rigid parts of the face, the resulting recognition algorithms are insensitive to changes in facial expressions. The facial contours are encoded using innovative pose invariant features, including Procrustean distances defined on pose-invariant curves. The extracted features are combined in a hierarchical manner to create three parallel face recognizers. Inspired by the effectiveness of region ensembles approaches, the three recognizers constructed around the nose tip and inner corners of the eyes are fused both at the feature-level and the match score-level to create a unified face recognition algorithm with boosted performance. The performances of the proposed algorithms are evaluated and compared with other algorithms from the literature on a large public database appropriate for the assumed constrained application scenario.     

基于轮廓线局部描述符的三维人脸识别

提出了一种基于等测地轮廓线的局部描述符来识别三维人脸。首先对三维人脸数据进行预处理, 得到统一的人脸区域并进行姿态归一化; 然后根据测地距离提取到鼻尖点相同距离的点组成等测地轮廓线, 对轮廓线进行重采样, 并对轮廓线上每个采样点的邻域提取局部描述符; 最后在建立测试人脸和库集人脸的点对应关系后进行局部描述符的加权融合和比较, 给出最终识别结果。算法在FRGC(face recognition grand challenge)v2. 0数据库上进行测试, 实验结果表明该方法具有较好的识别性能。     

基于人脸侧影线角点检测的鼻尖点定位方法

为实现人脸表情及姿态变化下,鼻尖点的快速准确定位,提出一种基于人脸侧影线角点检测的鼻尖点定位方法。首先利用柱状人头模型,进行人脸姿态粗矫正;然后通过旋转投影法提取人脸的侧影轮廓线,并基于B样条尺度空间检测侧影线角点,根据角点位置定位鼻尖点候选区域;最后根据鼻尖点的形状特征及凸出特性准确定位鼻尖点位置。在CASIA 3D和BOSPHORUS三维人脸数据库的实验结果表明,该方法对表情和姿态鲁棒性较好,且定位精度优于基于先验信息和基于统计模板的方法。     

A hierarchical dense deformable model for 3D face reconstruction from skull

3D face reconstruction from skull has been investigated deeply by computer scientists in the past two decades because it is important for identification. The dominant methods construct 3D face from the soft tissue thickness measured at a set of landmarks on skull. The quantity and position of the landmarks are very vital for 3D face reconstruction, but there is no uniform standard for the selection of the landmarks. Additionally, the acquirement of the landmarks on skull is difficult without manual assistance. In this paper, an automatic 3D face reconstruction method based on a hierarchical dense deformable model is proposed. To construct the model, the skull and face samples are acquired by CT scanner and represented as dense triangle mesh. Then a non-rigid dense mesh registration algorithm is presented to align all the samples in point-to-point correspondence. Based on the aligned samples, a global deformable model is constructed, and three local models are constructed from the segmented patches of the eye, nose and mouth. For a given skull, the globe and local deformable models are iteratively matched with it, and the reconstructed facial surface is obtained by fusing the globe and local reconstruction results. To validate the presented method, a measurement in the coefficient domain of a face deformable model is defined. The experimental results indicate that the proposed method has good performance for 3D face reconstruction from skull.