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.     

基于欧氏距离及向量内积的骨架提取算法

对骨架算法进行研究,提出一种骨架提取算法.通过对图像内部像素点进行距离变换得到其最近边界点的位置,将内部像素点到最近边界点的向量定义为边界向量,根据物体内部相邻边界向量的方向,计算每个像素点的内积值和其8邻域的最小内积值,得到的最小内积点,以确定的阈值从最小内积点中选取骨架种子点,再对骨架种子点进行处理,得到连通的骨架.试验证明这种算法能保证骨架具的完整性和连通性,正确反映物体的拓扑结构.     

Skeleton-based intrinsic symmetry detection on point clouds

We present a skeleton-based algorithm for intrinsic symmetry detection on imperfect 3D point cloud data. The data imperfections such as noise and incompleteness make it difficult to reliably compute geodesic distances, which play essential roles in existing intrinsic symmetry detection algorithms. In this paper, we leverage recent advances in curve skeleton extraction from point clouds for symmetry detection. Our method exploits the properties of curve skeletons, such as homotopy to the input shape, approximate isometry-invariance, and skeleton-to-surface mapping, for the detection task. Starting from a curve skeleton extracted from an input point cloud, we first compute symmetry electors, each of which is composed of a set of skeleton node pairs pruned with a cascade of symmetry filters. The electors are used to vote for symmetric node pairs indicating the symmetry map on the skeleton. A symmetry correspondence matrix (SCM) is constructed for the input point cloud through transferring the symmetry map from skeleton to point cloud. The final symmetry regions on the point cloud are detected via spectral analysis over the SCM. Experiments on raw point clouds, captured by a 3D scanner or the Microsoft Kinect, demonstrate the robustness of our algorithm. We also apply our method to repair incomplete scans based on the detected intrinsic symmetries.     

基于特征向量匹配的舞蹈实时姿态分析方法

针对人体运动姿态可自由编辑的特性,提取人体骨架模型,建立人体运动姿态模型库,分析了运动捕捉系统在舞蹈训练中的应用,提出基于特征平面间相似性匹配的方法来计算模型各部件间运动数据参数。经过验证,该方法对于人体姿态的分析具有较高的准确性、鲁棒性,使得舞蹈演员能够准确的对比出与标准舞蹈动作的差异,为舞蹈者进行科学舞蹈训练提供了理论支持。     

Robust skeletonization using the discrete λ-medial axis

Medial axes and skeletons are notoriously sensitive to contour irregularities. This lack of stability is a serious problem for applications in e.g. shape analysis and recognition. In 2005, Chazal and Lieutier introduced the λ-medial axis as a new concept for computing the medial axis of a shape subject to single parameter filtering. The λ-medial axis is stable under small shape perturbations, as proved by these authors. In this article, a discrete λ-medial axis (DLMA) is introduced and compared with the recently introduced integer medial axis (GIMA). We show that DLMA provides measurably better results than GIMA, with regard to stability and sensibility to rotations. We give efficient algorithms to compute the DLMA, and we also introduce a variant of the DLMA which may be computed in linear-time.     

一种快速的扫描铅笔稿图细化算法

二维动画计算机输助制作系统中,在对扫描铅笔稿图进行矢量化后,可以大大提高描线上色的效率,并且能够提取线条和闭包,对便于自动上色和中间帧生成等更高级功能的实现。扫描铅笔搞图的细化是矢量化的第一步,在比较了大量现存的图象细化算法后,提出了一种非迭代线跟踪细化算法,该算法效率较高,只需对图象进行一遍扫描加两遍轮廓跟踪,就能较好地满足二维动画计算机辅助制作系统对细化效率的要求。该文还对算法的时间复杂性进行     

基于SOAP技术构建Web服务的研究

简理分析了两个基于可扩展标记语言的技术：SOAP和WSDL的设计思想,并利用一个简单的实例，介绍了一种在Web服务开发过程中利用Tomcat和Axis自动编码、监听服务器和客户交互的方法。最后分析了在开发Web服务方面的几个有待解决的问题。     

非规则弯曲形变的不变量表示

摘要： 目的：全局描述不变量具有低维数和相似性测量简单的特点,本文针对于非规则弯曲形变图形,提出一种基于中轴骨架测地距离改进的全局描述不变量。方法：首先利用测地距离对于弯曲形变的不敏感性,修正图像质心位置,其次提取弯曲形变图像的中轴骨架代替图像全局域作为运算点集,并分配权重,降低计算复杂度,进而以此为基础提出一种单维度全局不变量。结果：实验结果表明该不变量具有良好的TRS不变性和弯曲形变不敏感性,相对其他传统特征表示方法,能够有效表示和鉴别非规则弯曲图形。结论：本文提出的单维度全局描述不变量,结构简单,计算方便。对于同类图像的弯曲变形,能够有效的进行区分,为该类图形的识别提供一种新的方法和思路。     

老年人室内危险行为监测预警系统研究

为保障老年人室内环境下的安全, 及时发现险情并提供救助支持, 本文开发了一套老年人室内危险行为监测预警系统, 其能够识别老年人常见危险行为, 并能进行预警。研究针对老年人常见危险行为中的异常俯身和跌倒, 基于RGB相机采集人体姿态信息并提取人体骨架的关键特征点; 利用支持向量机对各类危险行为进行分类识别; 进一步结合轨迹和定位信息向相关人员远程预警和紧急呼救。实验结果表明, 本系统对危险行为识别的真正类率达到97.14%, 能够较准确地完成老年人室内危险行为的监测预警, 从而有效减缓意外伤害的扩大, 保障老年人的居家安全。     

Learning hierarchical spatio-temporal pattern for human activity prediction

Human activity prediction has become increasingly valuable in many applications. This paper, initially from the perspective of cognition science, presents a novel approach to learning a hierarchical spatio-temporal pattern of human activities to predict ongoing activities from videos that contain only the onsets of the activities. Spatio-temporal pattern can be learned by a Hierarchical Self-Organizing Map (HSOM), which consists of two self-organizing maps (i.e., action map and actionlet map) connected via associative links trained by Hebbian learning. Ongoing activities can be predicted by Variable order Markov Model (VMM), which provides the means for capturing both large and small order Markov dependencies based on the training actionlet sequences. Experiments of the proposed method on four challenging 3D action datasets captured by commodity depth cameras show promising results.