快速非刚体人体运动三维重建

为了实现基于单目深度传感器的快速非刚体人体运动三维重建,提出一种基于骨架的非刚体人体运动点云融合算法.首先利用分割的人体局部点云配准,对深度传感器提取的人体骨架进行修正,提高了骨架提取的准确性;当相邻2帧之间存在较大人体运动时,利用骨架驱动人体表面点云进行点云粗配准;在粗配准的基础上,利用非刚体点云融合算法进行点云的精细配准,得到精确的表面重建.实验结果表明,该算法能够鲁棒地重建快速非刚体三维人体运动.     

基于三维图像动作识别算法研究

人体运动时的行为特征具有多样性和复杂性,无法采用精准的形状基描述人体行为的不确定性,进而无法构建人体三维运动模型,不能对人体三维图像动作进行准确的识别.传统方法假设人体运动的形状基数量稳定,人体运动行为具有复杂的形变特征,导致形状基参数出现波动,采用固定的形状基无法准确分析人体的复杂运动特征,使得人体三维图像动作识别存在较大的误差.提出一种Murkowski距离三维图像动作识别算法,依据人体运动时的物理特征将人体运动结构形状基参数处于Murkowski距离约束条件下,采用非线性优化方法进行求解获取人体三维行为特征,获取人体行为三维模型,进而实现对人体行为的准确判断.实验结果表明,改进算法能够对人体三维图像动作进行准确的识别,并且具有较高的精准度.     

基于雷达复杂1维距离数据的3维重建算法

基于刚体目标3维运动过程中的几何不变性,可以利用目标上多个散射点在单天线雷达1维距离像序列中的1维距离数据,重建出目标未知的3维结构和运动路径。针对此1维到3维的几何重构问题,提出了一种雷达刚体目标结构和运动的3维重建算法,该算法可利用散射点复杂的1维距离数据进行重建,并且采用非线性优化技术实现了对目标重建参数的捆绑调整(bundle adjustment)。另外,该算法中引入了目标的平移模型,使目标的平移参数能够与旋转参数一并求解,从而避免了距离对准操作的误差对重建精度的影响。仿真实验结果表明,由于重建数据中散射点的数量以及目标3维运动的丰富性得到了显著提高,尤其是最优化技术在算法中的成功应用,重建算法的鲁棒性得到了有效增强。     

基于图像序列的非刚体三维运动恢复

研究图像序列中非刚体的三维运动重建问题。介绍非刚体运动重建的两种重要算法:奇异值分解法和线性迭代法。对迭代算法所用的重构方法进行修改,在迭代过程中应用结果更为精确的重构方法来求解非刚体的模型和旋转矩阵。对真实图像序列的实验结果验证了该算法的有效性和精确性。     

基于MRF和神经网络的三维运动参数估计

为解决非刚体三维运动中运动参数估计的问题,结合了马尔科夫随机场(MRF)和神经网络的方法。其中,MRF用于建立各个特征点的局部运动相关性模型,求出各个特征点的三维坐标;神经网络方法用于对特征点进行聚类,并求出运动参数;最后根据求出的运动参数修正各个特征点的邻域系,实验结果表明该算法能够正确估计出非刚体的运动参数。     

基于特征点运动轨迹的非刚体三维运动恢复算法研究

研究了非刚体三维运动重建问题。介绍了基于轨迹空间理论的轨迹基变换算法,分析了轨迹基的频谱特性和非刚体特征点运动轨迹频谱特点,探讨了轨迹基的选择对非刚体三维重建的影响,并对真实图像序列的实验结果验证了该算法的有效性和精确性。     

物体三维图像运动重建算法仿真

在运动图像准确识别问题的研究中,在物体运动过程和背景较为复杂的情况下,物体的形变程度存在很大的随机性和不确定性,很难运用精确的形状基数量对非确定的形变加以约束.传统的非刚体物体三维图像重建算法中均为假设物体的形状基个数已知,没有运动物体形变复杂时,形状基参数估计错误带来的重建特征点缺失,影响三维图像重建真实性和重建清晰度.为解决上述问题,提出了一种散乱特征点碰撞的物体三维运动重建算法,运用动态图像序列中恢复的特征残缺的三维物体结构,在极小的特征空间内,通过散乱特征点间的碰撞联系,建立较为准确的补偿特征,对形状基估计不准进行补偿,弥补由于形状基估计不准带来的物体重建特征缺失、物体重建效果差、鲁棒性不强,不清晰的弊端.     

一种基于Hausdorff距离的运动物体跟踪算法

针对视频处理中运动物体的检测和跟踪问题,提出了一种基于Hausdorff距离的目标跟踪算法。新算法提出首先采用多尺度分水岭变换获取运动物体模型,消除了传统基于分水岭变换算法存在的缺陷;然后使用部分Hausdorff距离实现后续帧中运动物体模型的匹配;最后再次使用多尺度分水岭算法完成运动物体模型的更新。实验表明,该算法可以有效地跟踪多个刚体或非刚体目标。     

基于运动平滑性的动态图象序列的特征点对应

建立帧间的运动特征点对应是图象序列分析中的一项非常重要且非常困难的工作。根据图象序列的特点,该文提出了一种运动平滑的代价方程,并将运动平滑性与帧间特征点的欧氏距离相结合,以完成图象特征点运动轨迹的确立。由于此文的方法没有建立在运动的刚性约束之上,所以该方法同样适用于各种非刚体运动的特征点对应。     

SR-SIHKS：一种非刚体全局形状特征

非刚体由于姿态变化会产出多样的形变,因此非刚体的形状检索比刚体更具挑战性。形状特征提取是非刚体三维模型形状检索的关键问题。为了提高非刚体形状检索的准确度,提出了一种非刚体全局形状特征提取方法。此方法的核心思想是将稀疏表示（Sparse Representation,SR）理论用于对尺度无关的热核特征（Scale Invariant Heat Kernel Signature,SIHKS）进行稀疏编码,因此被称为SR-SIHKS。改进了SIHKS局部特征的提取方法,根据所处理的模型库来自适应地确定热扩散时间参数;采用K-SVD算法来训练字典,借助Batch-OMP算法实现局部特征的稀疏编码;将非刚体三维模型的所有局部特征的稀疏编码汇聚为全局形状特征。实验结果表明,SR-SIHKS具有比SIHKS和HKS更优的检索效果。     

The Singularity Principle and Property of Stewart Parallel Manipulator

Based on the kinematic relationship of rigid body, this paper presents a new principle and method to analyze the singularity of a Stewart parallel manipulator. We study the sufficient and necessary condition that three velocities of three non‐collinear points in a body can determine a screw motion. All singularities of the Stewart parallel mechanism are classified into three different linear‐complex singularities. The various algebraic and geometrical properties as well as kinematics ones are analyzed in detail in different singular configurations. With the condition above, the singularity loci and distribution characteristics of a 3/6—Stewart parallel manipulator for some orientations of the mobile are studied in an oblique plane and in three‐dimensional space. © 2003 Wiley Periodicals, Inc.     

运动图像序列的人体三维运动骨架重建

在计算机视觉领域 ,人体运动分析的研究具有相当广泛的应用前景 .由于人体运动的复杂性 ,已有的研究方法都对研究对象——人体 ,加上了许多限制条件 .文中提出了一种新的方法来获得各类人体运动的信息 .文中主要论述了该方法中对人体三维运动骨架的重建部分 ,其基本思想是在摄像机定标的基础上 ,应用三维人体模型知识和运动连续性依次建立每个图像的人体运动骨架 .最后给出了实验结果     

基于相机姿势全局运动估计及改进修复算法的视频稳定技术

在视频稳定的过程中,由于摄像机的运动,造成图像的扭曲.针对这种情况,提出一种基于相机姿势的全局运动估计,同时为了克服图像拼接后,部分区域像素丢失的问题,使用改进后调和模型来修复缺少的像素.算法首先提取特征不变量,然后基于这些特征不变量去估计摄像机的运动矢量,相乘各帧间的运动矢量,可以得到每一帧参考第一帧的运动矢量.运用这个矢量可以很好地计算出没有扭曲的图像.运用计算出的图像与视频帧进行拼接,可以很好的解决图像的扭曲的问题.然而,图像拼接完成后可能导致部分区域像素缺少,为了填充缺少像素,算法使用了改进的调和模型来修复缺少区域.实验结果表明,基于相机姿势的全局运动估计可以很好的解决图像扭曲的问题,同时改进的调和模型可以高效的完成对图像的修复.     

Visual Analysis of Trajectories in Multi‐Dimensional State Spaces

Multi‐dimensional data originate from many different sources and are relevant for many applications. One specific sub‐type of such data is continuous trajectory data in multi‐dimensional state spaces of complex systems. We adapt the concept of spatially continuous scatterplots and spatially continuous parallel coordinate plots to such trajectory data, leading to continuous‐time scatterplots and continuous‐time parallel coordinates. Together with a temporal heat map representation, we design coordinated views for visual analysis and interactive exploration. We demonstrate the usefulness of our visualization approach for three case studies that cover examples of complex dynamic systems: cyber‐physical systems consisting of heterogeneous sensors and actuators networks (the collection of time‐dependent sensor network data of an exemplary smart home environment), the dynamics of robot arm movement and motion characteristics of humanoids.     

基于立方体模型和EKF的运动汽车跟踪算法研究

针对固定摄像机、大范围复杂交通场景,提出了一种运动汽车的实时跟踪算法。根据汽车的刚体特性,采用立方体模型与运动汽车图像进行匹配的算法,避免三维重建的难题,能较为直观地得到运动汽车的形体信息。结合车辆的非线性运动特征引入EKF算法,准确地预测车辆的相关参数信息,减少目标跟踪过程中的搜索时间,从而能够实时准确地跟踪运动汽车目标。通过真实交通视频仿真实验,该算法具有较好的跟踪能力和抗干扰性能。     

Optimization-based key frame extraction for motion capture animation

In this paper, we present a new solution for extracting key frames from motion capture data using an optimization algorithm to obtain compact and sparse key frame data that can represent the original dense human body motion capture animation. The use of the genetic algorithm helps determine the optimal solution with global exploration capability while the use of a probabilistic simplex method helps expedite the speed of convergence. By finding the chromosome that maximizes the fitness function, the algorithm provides the optimal number of key frames as well as the low reconstruction error with an ordinary interpolation technique. The reconstruction error is computed between the original motion and the reconstruction one by the weighted differences of joint positions and velocities. The resulting set of key frames is obtained by iterative application of the algorithm with initial populations generated randomly and intelligently. We also present experiments which demonstrate that the method can effectively extract key frames with a high compression ratio and reconstruct all other non key frames with high quality.     

基于OBB树层次关系的相交体特征计算

针对不同复杂情况的网格模型在运动过程中发生的接触问题，提出了一个有效、准确的相交体特征计算算法，这里的特征包括相交三角形求交线，相交体求轮廓线，相交体求轮廓体。该算法以OBB（Oriented Bounding Boxes）树的数据结构为基础，借助AABB（Axis-Aligned Bounding Boxes）包围盒，通过分析线段、三角面、包围盒的位置关系情况，得到了相交线段、相交三角面以及包围三角面，并在此基础上计算出相应的相交体特征。该算法在CAD模型分割、建造、几何特征提取、生产车间以及机器人运动轨迹规划等方面都有很高的应用价值。     

基于联合运动补偿的边信息预测算法

传统块运动补偿算法仅利用单一运动向量场,该运动向量场中总会存在一定的运动异常,而过多的运动异常会严重衰退内插帧质量。为了解决该问题,提出了一种基于联合运动补偿的边信息内插算法,该算法使用双向运动估计计算出内插帧的运动向量场,接着采用当前块和其八个邻域块的运动向量联合预测出目标块。由于运动向量场的局部平滑特性会使八邻域块的运动向量十分接近当前内插块的真实运动向量,实验结果表明提出算法比传统算法有更好的容错性能。     

Automated enforcement for relaxed information release with reference points

Language-based information ftow security is a promising approach for enforcement of strong security and protection of the data confidentiality for the end-to-end communications. Here, noninterference is the standard and most restricted security property that completely forbids confidential data from being released to public context. Although this baseline property has been extensively enforced in various cases, there are still many programs, which are considered secure enough, violating this property in some way. In order to control the information release in these programs, the predetermined ways should be specified by means of which confidential data can be released. These intentional releases, also called declassifications, are regulated by several more relaxed security properties than noninterference. The security properties for controlled declassification have been developed on different dimensions with declassification goals. However, the mechanisms used to enforce these properties are still unaccommodating, unspecific, and insufficiently studied. In this work, a new security property, the Relaxed Release with Reference Points （R3P）, is presented to limit the information that can be declassified in a program. Moreover, a new mechanism using reachability analysis has been proposed for the pushdown system to enforce R3P on programs. In order to show R3P is competent for use, it has been proved that it complies with the well-known prudent principles of declassification, and in addition finds some restrictions on our security policy. The widespread usage, precision, efficiency, and the influencing factors of our enforcement have been evaluated.     

Fast and compact dynamic data compression based on composite rigid body construction

3D dynamic datasets compression still poses two challenges. One is high time cost due to growing data and complex computation of compression algorithms. The other is low compression factor because of complex motions of dynamic scenes and unknown motion equations. In this paper, composite rigid body construction for fast and compact compression of 3D dynamic datasets is proposed to solve these two problems. It accelerates the compression with a fast rigid body decomposition based on disjoint union, and avoids serial searching, comparing and merging of the rigid body decomposition. To increase the compression factor, composite rigid body is introduced with consideration of motion consistency among rigid bodies at different time periods. The results of the experiments show that our algorithm compresses dynamic datasets quickly and achieves a high compression factor.