基于运动矢量中心偏置的运动估计搜索策略

在对运动图像进行运动估计的时候,搜索策略的选择对运动估计的准确性、运动估计的速度影响重大。介绍一种基于运动矢量中心偏置的运动估计搜索策略,该搜索策略是根据运动矢量具有中心偏置分布的特点,以块误差函数最小作为调整搜索区域大小和位置的判断依据,从而实现准确的运动估计。详细叙述了算法的实现步骤,并通过实验比较,得出该算法在运算速度、信噪比方面的效果都较好。     

一种基于区域搜索的全局运动估计与补偿算法

开展全局运动估计与补偿研究是进行动态目标检测中的基础和前提。在总结现有运动估计与补偿方法的基础上,提出一种基于图像分割区域的运动性和大小的全局运动估计与补偿算法。首先,通过建立区域搜索的全局运动模型,同时进行区域定性分割和区域大小排序;然后,根据误差最小化准则在指定的分割区域中进行线性递归搜索,利用门限准则寻找出最佳的运动估计参数;最后,根据双线性内插法获得运动位移量。实验结果比较可知,所提算法较三步搜索算法(TSS)和全局搜索算法(FSA)等传统算法具有更高的准确性(图像平移帧差)和实时性(算法运行时间),能够很好地实现运动背景的全局校正。     

基于位平面匹配和卡尔曼滤波的视频稳定

针对数字视频帧间平移抖动的稳定问题,介绍一种基于局部求精位平面匹配运动估计和约束卡尔曼滤波运动校正的视频稳定算法。运动估计首先结合了灰阶比特平面匹配和菱形搜索策略得到初步的估计结果,然后在其附近再以最小绝对差（MAD）为测度,搜索更为准确的运动估计结果。这种运动估计方法在保证估计精度的前提下,显著地减少了运动估计需要的计算量。运动校正则考虑到实际稳像系统对校正量可能存在的某些约束,对绝对帧位移曲线采用约束卡尔曼滤波,得到平滑的位移曲线,有效地降低了帧间抖动的幅度,同时保证了校正矢量不超过稳像系统的实际校正能力。仿真实验表明,该算法具有精度高、速度快的特点,尤其适用于实时视频稳定。     

H.264标准半像素精度运动估计的硬件结构设计

设计了一种实时的基于可变块的半像素精度运动估计模块,包括半像素插值模块和半像素搜索模块,插值模块采用6阶FIR滤波器进行插值,搜索模块采用分级搜索算法.此模块应用在H.264标准便携视频设备的编码部分,用Verilog语言编写,采用Xilinx公司XC4VSX25的FPGA芯片作为硬件实现的运算核心.     

一种基于场景的非均匀校正算法

提出了一种基于场景的非均匀校正算法,它不仅可以消除红外焦平面阵列响应特性的 非均匀性,还可以补偿其漂移。建立了一个包含漂移因素的红外焦平面探测器响应模型,该模型构成了算法的基础。非均匀校正算法分两步执行:首先执行初步非均匀校正消除大部分的非均匀性,然后利用运动场景形成的红外图像序列来补偿响应特性的漂移噪声。场景运动估计是本算法的关键,块匹配方法被介绍来实现准确地运动估计。真实的红外图像数据说明了该算法的有效性。     

Reliable orientation estimation for mobile motion capturing in medical rehabilitation sessions based on inertial measurement units

Fully mobile and wireless motion capturing is a mandatory requirement for undisturbed and non-reactive analysis of human movements. Inertial sensor platforms are used in applications like training session analysis in sports or rehabilitation, and allow non-restricted motion capturing. The computation of the required reliable orientation estimation based on the inertial sensor RAW data is a demanding computational task. Therefore, an analysis of the computational costs and achievable accuracy of a Kalman filter and a complementary filter algorithm is provided. Highly customized and thus low-power, wearable computation platforms require low-level, platform independent communication protocols and connectivity. State-of-the-art small sized commercial inertial sensors either lack the availability of an open, platform independent protocol, wireless connectivity or extension interfaces for additional sensors. Therefore, an extensible, wireless inertial sensor called Institute of Microelectronic Systems Inertial Measurement Unit (IM)²SU, featuring onboard inertial sensor fusion, for use in home based stroke rehabilitation is presented. Furthermore, a Quaternion based, singularity free orientation estimation accuracy error measure is proposed and applied. To evaluate orientation estimation accuracy an optical system is used as golden reference. Orientation estimation based on a Kalman filter and a complementary filter algorithm is evaluated. The proposed IMU provides high orientation estimation accuracy, is platform independent, offers wireless connection and extensibility and is low cost.     

基于小波变换的分形随机信号的卡尔曼滤波

本文基于多尺度卡尔曼滤波方法来估计淹没在加性高斯白噪声中的分形布朗运动.针对每一尺度,给出了相应的动态系统参数和运动模型方程以及更精确的估计算法.并与多尺度维纳滤波进行了对比,计算机仿真结果证明了其优越性.     

Improved Pel-Recursive Motion Compensation

A pel-recursive motion estimation technique for television coding was introduced by Netravali and Robbins [1]. This method basically involves computing a motion displacement and then separating the pels into predictable and unpredictable segments. The addresses required to identify these segments and thus enable the motion estimation algorithm are transmitted along with pel error data. The original algorithms are slow to converge, i.e., many iterations are required to obtain an accurate displacement estimate. This research introduces extensions to the basic algorithm of [1] and offers two significant improvements. First, convergence speed is improved substantially, which means that the algorithms can better tolerate motion changes and diverse motion within the picture. Secondly, explicit address information is not required, as it is contained implicitly in the motion compensation algorithm. For the sequences examined, this method proved superior to that of explicitly transmitting the address data. This algorithm has much better convergence rates and has prediction rates better than the original.     

Is it feasible to reconstruct body segment 3-D position and orientation using accelerometric data?

The analysis of the mechanics of the musculo-skeletal system during the execution of a motor task requires the determination of the instantaneous position and orientation of the body segments involved in relation to an inertial system of reference. By using adequately assembled uniaxial accelerometric sensors, an easy-to-manage measurement system can be obtained that estimates the three-dimensional position and orientation (P&O) of a body segment through an appropriate analytical model. However, the extent to which experimental errors, in particular accelerometers (ACs) assembly inaccuracies, affect such estimation has never been systematically investigated. This paper systematically analyzes the sensitivity of analytical models of body segment P&O reconstruction through a six-AC system and a nine-AC system to different sources of experimental error. We simulated and statistically assessed the performance of these models in the case of body segment motions typical of movements under muscular control. The results obtained indicated that the inaccuracy in the orientation of the individual AC's active axes and the offset error in the AC responses were the major sources of P&O estimation errors. In particular, no accurate estimation of position was possible with the analytical models analyzed. Under the motion conditions simulated in this study, no substantial advantages were found in using a nine-AC system rather than a six-AC system. Considering that the magnitudes of the simulated experimental errors were quite low (< or = 0.1 deg: AC's orientation; < or = 10(-4) m: uncertainty of the distance between two ACs; < or = 10(-2) ms(-2): random error; 0.5 x 10(-2) ms(-2): offset error), the results indicate that none of the two ACs systems analyzed is suitable for body segment P&O estimation in routine biomechanical applications.     

在人体运动测量中应用四元数扩展卡尔曼滤波

提出了一种适合多运动传感器方位测定系统的四元数扩展卡尔曼滤波,该方位测定系统适合人体运动领域的研究,它是基于iNEMO整合套件,集成了三轴陀螺仪、三轴加速度计和三轴磁强计。在该文的扩展卡尔曼滤波过程中,通过加速度计、磁力计的量测噪声进行陀螺仪角度修正,使测量角度值逐渐逼近真实角度大小,同时量测噪音的协方差矩阵设计,可以使方位测定系统辨别静止和运动,增加了可靠性。结合人体前臂屈伸运动的测试,验证了算法的有效性,加之其小尺寸、多功能、低功耗的特点,证明基于MEMS的运动传感器在人体运动测量领域的应用前景良好。