基于相对形变模型及正则化技术的人体运动估计

为了使根据人体行走的单目动态图象序列，对人体手臂及腿部的运动及结构参数进行估计的结果更为可信、更具鲁棒性，提出了一种基于相对形变模型及正则化技术的人体运动估计方法，该方法首先在物体中心坐标的运动表示方式下，通过在刚体运动模型中加入形变系数的方法给出了基于相对形变概念的非刚体运动模型；然后，根据这一非刚体运动模型进行正则化运动及结构参数的估计，再以正则化的形式融入人体运动的先验知识，使运动估计的结果更具鲁棒性，实验结果证明，该方法有效地反映了人体的非刚体运动模式，运动模型中所加入的相对形变系数也一定程度反映了人体的运动规律。     

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。     

从二次曲线对应恢复刚体三维运动和结构

研究从二次曲线恢复刚体的三维运动参数和结构参数问题.建立了基于二次曲线的几何模型和运动模型,从理论上证明最少需要3条对应的二次曲线,建立一个由6个非线性方程构成的非线性方程组.能求出刚体的旋转运动参数和包含一个比例因子(不等于零)的平移运动参数.在此基础上得到空间二次曲线的参数,对应于每一组运动参数,空间二次曲线的参数有两个解.     

基于Murkowski距离连续的非刚体三维运动恢复算法研究

现有的非刚体三维运动重建算法很难根据不同的场景、不同的非刚体来寻找不同的形状基,这种情况对重建 过程产生了很大的影响,造成模型失真。为了解决这一问题,提出一种基于Murkowski距离连续的非刚体三维运动 恢复算法,该算法根据在高速分解的图像序列中帧与帧之间的运动参数与特征点位移变化都呈现连续平缓的物理特 性,在Murkowski距离约束的情况下,将运动结构参数通过非线性优化的方法来进行求解,最终得到非刚体的三维运 动结构,并且通过仿真实验,验证了它的可行。     

基于广义形态内插的非刚体运动描述方法

提出一种基于形态变换的非刚体运动的广义内插方法.通过对非刚体的凸剖分及凸子集全局优化匹配,与传统的线性内插方法相比,解决了任意非同拓扑结构(包括有孔及凹多边形)的内插问题.理论证明,此种内插方法是一种全局优化的内插方法,并证明了此方法的正确性,讨论了不同凸剖分对内插的影响,把非刚体的运动分解为非刚体的变形与刚体的旋转.实验证明,此内插方法效果自然,质量好,速度快,可用于非刚体运动描述及二维动画关键帧的内插.     

刚体空间运动参数估计

本文发展了一种模型匹配估计算法,它具有较高的鲁棒性.根据已做的总数达一千二百万个不同空间点的实验显示:在采样总数N≤30时,只要有4到5对匹配正确的点就可以准确地估计出刚体空间运动的参数.这种高鲁棒性使得该方法能够用于多个刚体运动的分析.     

人脸序列图象的头部运动参数估计

在人脸序列的图象编码中 ,由于模型基编码方法可以获得高的主观图象质量和低的码率 ,因而受到广泛重视 .但是 ,其运动参数的可靠估计还是一个难点 .为此 ,该文分析了头部运动的特点 ,并把它分为头部刚体运动、脸部表情的简单运动和脸部表情复杂运动 3种形式 .其中 ,提取头部刚体运动参数利用了基于特征点对的运动参数估计算法 ,并提出了一个线性的实现方法 ;文中还指出提高运动参数估计的精度在于选择合适的特征点和建立一个和特定人脸相一致的三维线框模型 ;另外 ,还为脸部表情的简单运动建立了形变矩阵 ;最后给出了用面积误差函数评价的运动参数估计误差 .     

用二维点对应数据分割和估计多刚体运动

已知含有多个三维刚体的场景,在运动前后的二维点对应数据集合,其中可以包 含高斯噪声和出格点数据,发展了初始部分匹配的生成-生长技术并运用刚性约束.将上述 二维点对应数据集合.分割成多个分别对应于不同刚体运动的二维点对应数据子集,并能分 离出所有出格点数据.再利用单刚体运动估计算法就可估计出各个刚体运动参数.实验结果 表明了算法的有效性.     

利用数字视频技术测量旋转速度的研究

基于视频的测量系统,具有非接触,安装维护简捷而且费用低等特点;本研究的目标就是利用摄像机对测量对象进行视频采集,然后提取相邻两帧图像;当运动对象进行简单的单轴旋转时,利用Hough变换(或Rando变换)技术进行直线的角度检测;计算出相邻帧的角度差,根据间隔时间,计算出角速度;当球体进行多轴旋转时,根据球体标志投影,结合三维空间刚体运动模型,利用一组特征点坐标,采用两步迭代交替估计运动参数,求得运动物体相对三维空间各个轴的角速度;并对特殊已知结构参数的运动物体给出了简化的计算方法,通过实验表明本方法测量结果满足要求.     

采用测地线活动轮廓模型检测与跟踪运动目标

水平集几何活动轮廓模型能较好地适应曲线的拓扑变化.为了跟踪和获取刚体和非刚体运动目标的轮廓信息,提出了一种基于改进测地线活动轮廓(GAC)模型和Kalman滤波相结合的算法以检测和跟踪运动目标.该算法首先采用高斯混合模型和背景差分获取目标的运动区域,在运动区域内采用引入距离规则化项的GAC模型进行曲线演化,使改进GAC模型在运动目标的真实轮廓处收敛;然后通过结合Kalman滤波预测目标下一帧的位置,实现对目标轮廓跟踪.实验结果表明,该方法适用于刚体和非刚体目标,在部分遮挡的情况下也能保持良好的检测和跟踪效果.     

Reconstruction of non-rigid 3D shapes from stereo-motion

Several non-rigid structure from motion methods have been proposed so far in order to recover both the motion and the non-rigid structure of an object. However, these monocular algorithms fail to give reliable 3D shape estimates when the overall rigid motion of the sequence is small. Aiming to overcome this limitation, in this paper we propose a novel approach for the 3D Euclidean reconstruction of deformable objects observed by an uncalibrated stereo rig. Using a stereo setup drastically improves the 3D model estimation when the observed 3D shape is mostly deforming without undergoing strong rigid motion. Our approach is based on the following steps. Firstly, the stereo system is automatically calibrated and used to compute metric rigid structures from pairs of views. Afterwards, these 3D shapes are aligned to a reference view using a RANSAC method in order to compute the mean shape of the object and to select the subset of points which have remained rigid throughout the sequence. The selected rigid points are then used to compute frame-wise shape registration and to robustly extract the motion parameters from frame to frame. Finally, all this information is used as initial estimates of a non-linear optimization which allows us to refine the initial solution and also to recover the non-rigid 3D model. Exhaustive results on synthetic and real data prove the performance of our proposal estimating motion, non-rigid models and stereo camera parameters even when there is no rigid motion in the original sequence.     

一种基于在线模型匹配与更新的人脸三维表情运动跟踪算法

提出一种基于在线模型匹配与更新的人脸三维表情运动跟踪算法。利用自适应的统计观测模型建立在线模型,自适应的状态转移模型结合改进的粒子滤波同时进行确定性搜索和随机化搜索,并且融合目标的多种测量信息减少光照和个体相关性的影响。利用所提出的算法既可以得到全局刚体运动参数,又可以得到局部柔性表情参数。实验证明了该算法的有效性。     

Recovery of nonrigid motion and structure

The authors introduce a physically correct model of elastic nonrigid motion. This model is based on the finite element method, but decouples the degrees of freedom by breaking down object motion into rigid and nonrigid vibration or deformation modes. The result is an accurate representation for both rigid and nonrigid motion that has greatly reduced dimensionality, capturing the intuition that nonrigid motion is normally coherent and not chaotic. Because of the small number of parameters involved, this representation is used to obtain accurate overstrained estimates of both rigid and nonrigid global motion. It is also shown that these estimates can be integrated over time by use of an extended Kalman filter, resulting in stable and accurate estimates of both three-dimensional shape and three-dimensional velocity. The formulation is then extended to include constrained nonrigid motion. Examples of tracking single nonrigid objects and multiple constrained objects are presented     

Humanoid Robotic System with and without Elasticity Elements Walking on an Immobile/Mobile Platform

This work is concerned with the modeling and analysis of a complex humanoid robotic system walking on an immobile/mobile platform. For this purpose, a software package was synthesized which allows one to select configuration of both the humanoid and the platform. Each joint of the biped and platform can be defined by the user via the motor state (active or locked) and gear type (rigid or elastic). The user can also form very diverse configurations of the humanoid and platform. The software package forms a mathematical model. By selecting system’s parameters the simulation allows user to analyze dynamic behavior of the biped of selected configuration, walking on either an immobile or mobile platform of selected configuration. In the moment when the biped steps on the platform, the latter, by its dynamics, acts on the biped dynamics, and the biped on the other hand, by its characteristics, influences dynamics of the platform motion. These two complex contacting systems form a more complex system, whose mathematical model has to encompass all the elements of coupling between the humanoid joints and platform joints. The phenomenon of coupling is analyzed first on a humanoid robotic system with all rigid elements, which is in contact with the platform mechanism having also all rigid elements. It has been shown that coupling is more influenced when elasticity elements are included into the configuration. Insufficient knowledge of coupling characteristics may present a serious disturbance to the system in the robotic task realization. The deviation of the ZMP (Zero-Moment Point) from the reference trajectory is presented, which implies the need for the synthesis of new control structures for stabilizing biped motion on the immobile/mobile platform. The reference trajectory may be defined in very different ways and from several aspects. Reference trajectory of each joint can be defined so to encompass or not encompass elastic deformations. The control structure for the biped walking on the platform should be defined so that it satisfies the requirement for the ZMP to be within the given boundaries in every sampling instant, which guarantees dynamic balance of the locomotion mechanism in the real regime. The control is defined as CR (Centralized Reference control, calculated from the reference state), plus LO (control via local feedbacks of motor motion with respect to position and velocity). In the case of the biped motion on a mobile platform CR control is defined separately under the real conditions of unknown characteristics of coupling between the two complex systems, as well as unknown elasticity properties. The analysis of simulation results of the humanoid robot motion on a mobile platform gives evidence for all the complexity of this system and shows how much system parameters (choice of trajectory, configuration, geometry, elasticity characteristics, motor, etc.) influence stabilization of its humanoid motion.     

Modeling and System Identification of the muFly Micro Helicopter

An accurate mathematical model is indispensable for simulation and control of a micro helicopter. The nonlinear model in this work is based on the rigid body motion where all external forces and moments as well as the dynamics of the different hardware elements are discussed and derived in detail. The important model parameters are estimated, measured or identified in an identification process. While most parameters are identified from test bench measurements, the remaining ones are identified on subsystems using the linear prediction error method on real flight data. The good results allow to use the systems for the attitude and altitude controller design.     

基于神经网络的运动参数估计

分别就两种约束使用神经网络对三维刚体运动进行参数估计.一是基于三维点匹配,将预测的运动参数作用于运动前的坐标,与运动后坐标进行比较;二是基于二维运动场,将使用预测的运动参数计算得出的二维运动场与图像序列中计算得出的二维运动场进行比较.两个神经网络均使用Newton-Raphson方法更新权值,以达到目标误差最小化.通过实验验证了该神经网络方法.     

Graphics processing unit (GPU) accelerated fast multipole BEM with level-skip M2L for 3D elasticity problems

In order to accelerate fast multipole boundary element method (FMBEM), in terms of the intrinsic parallelism of boundary elements and the FMBEM tree structure, a series of CUDA based GPU parallel algorithms for different parts of FMBEM with level-skip M2L for 3D elasticity are presented. A rigid body motion method (RBMM) for the FMBEM is proposed based on special displacement boundary conditions to deal with strongly singular integration and free term coefficients. The numerical example results show that our parallel algorithms obviously accelerates the FMBEM and can be used in large scale engineering problems with wide applications in the future.