关节特征约束的3维模型骨架提取算法

根据多分辨率Reeb图（MRG）的原理,提出一种基于关节特征约束的骨架优化算法。它克服了基于曲率约束提取骨架方法中逐点计算顶点的曲率约束轮廓的低效性,通过分析网格顶点的离散高斯曲率,获取模型表面上具有凹陷特性的双曲极值点作为约束点, 进行关节特征区域的有效提取。进而增加关节特性点,优化MRG骨架。实验结果表明,本方法有效地突出了模型的拓扑分支特征以及模型表面的细节,提高了骨架提取的精度和效率。     

On the extraction of 3D models from airborne video sensors for geolocation

Geolocation of a feature in a video sequence collected from a moving platform is an activity that must be undertaken in video exploitation, especially surveillance and reconnaissance applications. Examples of sensor systems that are the focus of this work include manned and unmanned aerial vehicles. The approach described here uses positional information from three sources to compute refined coordinates in three dimensions for any feature in the video sequence. These three sources are: first, sensor-platform metadata describing the likely sensor footprint based on sensor-platform positional and attitudinal information; second, 3D information of a scene inherent in a video sequence collected from a moving platform; and third, reference imagery of the region of interest that is geolocated and georectified such as aerial photography. We describe the overall steps involved in this process and the progress made to date.     

Inverse lagrangian dynamics for animating articulated models

This paper presents the application of inverse Lagrangian dynamics for the purpose of animating articulated models. The method orginates from mechanics and robotics and has been adapted to deal with branched kinematic chains and joints with multiple degrees of freedom. The method is then reformulated to calculate the ground reaction forces that apply to the body. The approach is direct and does not involve guesswork. The formulation has been implemented into a general animation system that is entirely interactive and supports the facility of simulating generic articulated models.     

Optimized keyframe extraction for 3D character animations

In this paper, we propose a new method to automatically extract keyframes from animation sequences. Our method can be applied equally to both skeletal and mesh animations. It uses animation saliency computed on the original data to help select the group of keyframes that can reconstruct the input animation with less perception error. For computational efficiency, we perform nonlinear dimension reduction using locally linear embedding and then carry out the optimal search in much lower‐dimensional space. With this approach, reconstruction of the animation from the extracted keyframes shows much better results as compared with earlier approaches. Copyright © 2012 John Wiley & Sons, Ltd.     

Skeleton-enhanced line drawings for 3D models

We present a novel line drawing approach for 3D models by introducing their skeleton information into the rendering process. Based on the silhouettes of the input 3D models, we first extract feature lines in geometric regions by utilizing their curvature, torsion and view-dependent information. Then, the skeletons of the models are extracted by our newly developed skeleton extraction algorithm. After that, we draw the skeleton-guided lines from non-geometric regions through the skeleton information. These lines are combined with the feature lines to render the final line drawing result using the line optimization. Experimental results show that our algorithm can render line drawings more effectively with enhanced skeletons. The resulting artistic effects can capture the local geometries as well as the global skeletons of the input 3D models.     

Robust shape normalization of 3D articulated volumetric models

3D shape normalization is a common task in various computer graphics and pattern recognition applications. It aims to normalize different objects into a canonical coordinate frame with respect to rigid transformations containing translation, rotation and scaling in order to guarantee a unique representation. However, the conventional normalization approaches do not perform well when dealing with 3D articulated objects.To address this issue, we introduce a new method for normalizing a 3D articulated object in the volumetric form. We use techniques from robust statistics to guide the classical normalization computation. The key idea is to estimate the initial normalization by using implicit shape representation, which produces a novel articulation insensitive weight function to reduce the influence of articulated deformation. We also propose and prove the articulation insensitivity of implicit shape representation. The final solution is found by means of iteratively reweighted least squares. Our method is robust to articulated deformation without any explicit shape decomposition. The experimental results and some applications are presented for demonstrating the effectiveness of our method.     

任意姿态虚拟人网格模型骨骼提取算法

人体骨骼动画技术是虚拟人物建模中的研究重点。在现有人体骨骼动画的制作过程中,动画师必需手工标定人体各主要关节点位置及人体骨架每一关键帧的姿态,工作量巨大。因此提出一种自动提取人体任意姿态网格模型骨架结构的方法。该方法首先利用模型各顶点间测地距离的几何关系自动识别人体位于四肢和头顶末端的5个特征点,再以特征点为起点生成等测地距离曲线族,利用等测地距离曲线将人体四肢和躯干区分开来,将这些相邻等测地线中心连接起来生成5条骨骼中心线,最后在中心线上根据中心夹角极小值及等测地距离曲线似圆率来确定人体关节的确切位置。实验结果表明,该算法能适应不同姿态的人体模型,计算结果准确性高,能完全自动实现关节点定位和骨骼提取。     

3DMax中角色动画技术

在一个动画电影中,剧本的创新他造和动画角色的设计是灵魂,观众对动画角色的价值判断不仅仅是停留在表面的造型,而且还包括对剧本背景及角色内涵的认同。角色表现出一个人的内在和外部造型。所以一个动画片的成功与否,与角色动画技术有点至关重要的关系。     

人体骨架模型的建立

人体运动分析在计算机视觉研究领域中具有广泛的应用前景。人体骨架包含了很多的人体运动信息,且简单明了,所以对人体骨架提取具有很重要的意义。本文提出了一种人体骨架模型的建立方法,该方法在骨架提取方面有较强的去噪和抗干扰能力,有很好的鲁棒性,可提取更加有效的骨架图像,进一步结合人体解剖学的基础,建立了人体骨架模型,为人体特征识别(HID)和运动人体的实时追踪打下了坚实的基础。     

具有鲁棒性的图像骨架提取方法

基于最大正方形的中轴变换,提出了一种二值图像的骨架提取算法。首先通过计算目标像素邻域内最大正方形的所有像素的个数来进行中轴变换,判断骨架点,并提取骨架。如果通过设定一个阈值,再提取骨架,就可以滤除背景中的噪声。实验结果表明:该方法提取的骨架效果好,通过与基于传统中轴变换和形态学提取骨架方法进行比较,该方法抗干扰能力强。     

交互式轮廓线骨架的提取

为精确抽取自由绘制的二维轮廓线骨架,提出了一种新的自适应骨架提取方法.将用户绘制的轮廓线,采用离散曲率约束,自适应调整步长,提取样点,进行最小二乘法实现样条曲线拟合,有效地突出了曲线形状特征;依据曲线模型的特征点,改进约束化三角剖分方法,高效地重建三角网格的拓扑结构;基于Voronoi图优化提取轮廓线骨架.实验结果表明了该算法的高效性和鲁棒性.     

Automatic pose-independent 3D garment fitting

Given a virtual garment model on a reference human model, we propose an automated 3D garment fitting system that fits the garment model to a target human model. The proposed method can transfer garment models between human models without any user guidance even when the reference and target human models have different poses. Our goal is not to resize or deform the original garment model according to the target human model but to yield realistic fitting results of the given garment on the target human models. Using pose-independent segmentation and cloth simulation, we achieve realistic and automatic fitting results in reasonable running time. Our method can replace the time-consuming manual fitting process that is necessary for many applications that use virtual garments, such as games, animations, CAD tools and online clothing stores.     

保持物理特征的三维标量场拓扑简化

针对现有三维标量场拓扑简化方法,在简化的同时可能丢失部分有意义的物理特征问题,提出并实现了一种保持物理特征的三维标量场拓扑简化算法,采用为应用定制的物理判据分类标量场区域,将标量场重要特征检出和拓扑简化关联起来。结合Morse理论在次要物理特征所在区域构造Morse-Smale复形,并通过对复形上一系列临界点对的删除,达到简化和平滑函数拓扑特征的目的。实验结果验证了该方法的可行性。     

Retrieving articulated 3-D models using medial surfaces

We consider the use of medial surfaces to represent symmetries of 3-D objects. This allows for a qualitative abstraction based on a directed acyclic graph of components and also a degree of invariance to a variety of transformations including the articulation of parts. We demonstrate the use of this representation for 3-D object model retrieval. Our formulation uses the geometric information associated with each node along with an eigenvalue labeling of the adjacency matrix of the subgraph rooted at that node. We present comparative retrieval results against the techniques of shape distributions (Osada et al.) and harmonic spheres (Kazhdan et al.) on 425 models from the McGill Shape Benchmark, representing 19 object classes. For objects with articulating parts, the precision vs recall curves using our method are consistently above and to the right of those of the other two techniques, demonstrating superior retrieval performance. For objects that are rigid, our method gives results that compare favorably with these methods. A preliminary version of this article was published in EMMCVPR 2005. In this extended version we have included results on the significantly larger McGill Shape Benchmark, making a stronger case for the advantages of our method for models with articulating parts. We have also included expanded introduction, medial surface computation, matching, indexing, experimental results, and discussion sections, along with several new figures.     

保特征的点云骨架提取算法

三维模型的骨架提取是计算机图形学中一个重要的研究方向。对于有噪声的点云模型,曲线骨 架提取的难点在于保持正确的拓扑结构以及良好的中心性;对于无噪声的点云模型,曲线骨架提取的难点在于 对模型细节特征的保留。目前主流的点云骨架提取方法往往无法同时解决这 2 个难点。算法在最优传输理论的 基础之上结合聚类的思想,将点云骨架提取的问题转化为一个最优化问题。首先使用最优传输得到原始点云与 采样点云之间的传输计划。然后使用聚类的思想将原始点云进行分割,采样点即成为了簇的中心。接着通过簇 与簇之间的调整与合并减少聚类个数,优化聚类结果。最后通过迭代的方式得到粗糙的骨架并使用插点操作进 行优化。大量实验结果表明,该算法在有噪声与无噪声的三维点云模型上均能提取出质量良好的曲线骨架并保 留模型的特征。     

基于人体特征三维人体模型的骨架提取算法

实现骨骼动画的一个前提是获取人体模型的骨架,现有的骨架提取算法不是计算复杂度高,就是提取准确度不高,或者需要手工干预.提出一种基于人体特点和黄金比例律的人体模型骨架提取算法,首先对模型进行精简,然后根据人体的特点与黄金比例律确定模型关节点的大概位置,在此基础上对模型进行分割.由于人体存在个体差异且姿势也可能不一致,采用测地距离方法对关节点的位置进行修正,确定其位置.与现有的算法相比,本方法效率高,同时实验显示本算法具有更好的骨架提取效果.     

透视投影下三维运动重建

单相机下，三维信息的恢复往往呈现出病态，如何在透视投影约束下恢复高质量的三维人体运动信息是计算机视觉领域一个具有挑战性的课题。提出一个扩展模型，即如何从起点出发，依次扩展到得三维空间中人体关节点的位置，从而恢复出运动信息。相对于已有的算法，提出在搜索空间中用一组最优准则得到连续平滑的扩展起点，并且在扩展过程中利用全局运动平滑假设，有效地消除了深度信息恢复时固有的二义性。最后，将结果运用于动画制作，验证提出的算法的有效性。     

计算机生成三维卡通风格喷水效果

在过去20年中人们提出许多处理水运动的模型，但大都致力于生成真实感的动画，而对传统手工绘制的水运动效果建模问题几乎无人涉及，给出一个自动生成三维卡通风格喷水效果的计算机模型，首先介绍如何从手工绘制的卡通喷水画面中提取它的骨架，然后沿骨架用等级结构定义喷水边线、水波纹理与水滴，通过引进随机分量控制，本模型可以自动生成无重复机械感的并与卡通风格一致的三维卡通风格喷水序列画面。