模型基编码中的运动估值研究

在介绍模型编码基本原理的基础上,着重介绍了语义基编码,对它的运动估值技术作了详细分析,并用光流法对运动图像进行了运动估值,对该估值算法作了评价和展望。     

STi3220在视频压缩编码中的应用

介绍运动估值专用芯片ＳＴｉ３２２０的工作原理，分析了利用ＳＴｉ３３２０实现实时运动估值时所需要的视频数据控制方法，并讨论了适用于ＭＧＥＧ１的运动估值实现方案。     

电视系统中的运动检测和运动估值

在电视系统中，为改善图像质量或压缩信号频带，往往引入运动检测、运动估值（ＭＥ）和运动补偿（ＭＣ）技术。本文主要介绍现行电视系统、模拟高清晰度电视系统和数字高清晰度电视系统中常用的运动检测和运动估值方法。     

矩分层运动估值法

介绍了一种利用矩进行分层的运动估值方法，在保证全局最优解的同时，使运算量较采用ＭＡＤ准则的穷尽搜索法（ＦＳＭ）大为降低。     

亚象素运动估值快速算法

高精度的匹配和补偿可以减少预测误差，提高视频图像的压缩效果。文中提出了一种亚象素精度视频运动估值的快速算法，根据半象素精度运动估值的中间结果，直接推算出更高精度的运动估值。该算法为高精度亚象素运动估值的研究提供了算法保证。     

基于运动矢量插值的运动补偿算法

本文首先研究了相关性约束运动估值算法,然后提出了基于运动矢量插值的运动估值算法,实验表明新算法的预测性能明显比传统块匹配运动估值算法(BMA)好,而且预测图象的主观质量得到显著改善。     

基于运动矢量插值的运动补偿算法

本文首先研究了相关性约束运动估值算法，然后提出了基于运动矢量插值的运动估值算法，实验表明新算法的预测性能明显一比传统块匹配运动估值算法（ＢＭＡ）好，而且预测图象的主观质量得到显著改善。     

利用定向观测量估计飞机目标的运动

本文介绍了空对空跟踪情况下估计强机动飞机目标运动的一种新方案。研制了一种相互作用滤波器系统,该系统根据目标视线角数据,通过调节运动状态滤波器的估值,提供改善了的目标运动状态估值。设想以与光电跟踪器一起使用的图形识别技术来提供目标的方向信息。目标定向滤波器通过用当前目标运动的最佳估值对测得的视线角进行统计加权来处理视线角的观测值。应用空气动力学升力方程来建立近似攻击角与目标速度和加速度的关系,也研究了飞机目标法向加速度的新颖统计模型,以便更好地表示未知目标的加速度。为评价相互作用滤波器系统的性能,还提供了真实三维情况的仿真结果。     

高清晰度电视运动估值方案的研究

在分析了现行HDTV运动估值方案的基础上,提出了一种基于快速预测搜索算法的HDTV运动估值方案,其性能优于其它方案。     

模型基编码中的脸部运动估值研究

主要针对模型基编码方案的运动参数估值问题，运用3维运动估值的方法，推导出运用于人脸运动参数估值的运动模型和光流算法，并对该算法的效果进行分析，对算法的改进提出算法。     

Improvement of region-based motion estimation by considering uncovered regions

In natural video sequences, object movement causes regions to be covered or uncovered. Conventional algorithms for region-based motion estimation do not take uncovered regions into full account. Uncovered regions seriously decrease the accuracy of motion estimation. This paper presents an algorithm for increasing the motion estimation accuracy. This algorithm detects uncovered regions and uses them to improve image segmentation and motion estimation. Experimental results show that the presented algorithm is effective in reducing the displaced frame difference, without introducing any extra information for coding applications.     

运动估计技术在图像匹配中的应用

在运动估计技术的基础上提出了一个巡航导弹制导系统中图像匹配问题的解决方案，及其具体实现。实验证明这种硬件电路能够实时实现灰度 匹配。     

基于运动矢量多级分析的视频全局运动估计

基于运动矢量场的视频全局运动估计相较于基于像素的估计方法具有较低的计算复杂度,因而广泛应用于视频分割及视频压缩等领域中。然而噪声和前景目标等外点区域的存在,降低了全局运动估计的准确性。为了提高全局运动估计的准确度,该文提出一种基于运动矢量多级分析的全局运动估计算法,该算法根据局部运动与全局运动的运动特性差异自适应地滤除前景目标区域,由邻域矢量间相似性度量检测出纹理平滑周期区域,最后滤除孤立的噪声区域,由滤波得到的内点区域求解全局运动参数。实验结果表明,该方法能有效地滤除外点区域,提高全局运动估计的准确性。     

Motion-based region growing segmentation of image sequences

This paper proposes a motion-based region growing segmentation scheme for the object-based video coding, which segments an image into homogeneous regions characterized by a coherent motion. It adopts a block matching algorithm to estimate motion vectors and uses morphological tools such as open-close by reconstruction and the region-growing version of the watershed algorithm for spatial segmentation to improve the temporal segmentation. In order to determine the reliable motion vectors, this paper also proposes a change detection algorithm and a multi-candidate pro- screening motion estimation method. Preliminary simulation results demonstrate that the proposed scheme is feasible. The main advantage of the scheme is its low computational load.     

Fine‐Motion Estimation Using Ego/Exo‐Cameras

Robust motion estimation for human–computer interactions played an important role in a novel method of interaction with electronic devices. Existing pose estimation using a monocular camera employs either ego‐motion or exo‐motion, both of which are not sufficiently accurate for estimating fine motion due to the motion ambiguity of rotation and translation. This paper presents a hybrid vision‐based pose estimation method for fine‐motion estimation that is specifically capable of extracting human body motion accurately. The method uses an ego‐camera attached to a point of interest and exo‐cameras located in the immediate surroundings of the point of interest. The exo‐cameras can easily track the exact position of the point of interest by triangulation. Once the position is given, the ego‐camera can accurately obtain the point of interest's orientation. In this way, any ambiguity between rotation and translation is eliminated and the exact motion of a target point (that is, ego‐camera) can then be obtained. The proposed method is expected to provide a practical solution for robustly estimating fine motion in a non‐contact manner, such as in interactive games that are designed for special purposes (for example, remote rehabilitation care systems).     

图像的区域描述方法及运动估计

文中提出一种任意形状区域的图像描述方法进行图像序列的运动估计。首先,对初始帧图像采用保边界平滑,然后,对平滑帧进行分水岭分割。根据标记图像,将图像以区域邻接图的方式进行存储。为解决过度分割的问题,给出了区域的灰度特性和边界强度及区域尺寸相结合的融合准则。最后,每个区域采用仿射运动模型及非线性最小均方法进行参数优化。得到的运动矢量场同基于像素点的估计方法相比具有更高的一致性和抗干扰性,运动补偿差图像的峰值信噪比得以提高。     

Robust motion estimation for night-shooting videos using dual-accumulated constraint warping

This paper introduces a novel concept of dual-accumulated constraint projection warping, as a robust and efficient motion estimation solution for night video stabilization. Small imaging-sensors used in compact hand-held cameras become very prone to noise and blur under low illumination condition. Restricted lighting results in dark boundaries and degrades textural information of the frame. Presence of these combined textural artifacts makes night-shooting a hard problem for accurate motion estimation. At poor lighting, local intensity variations result in failure of inter-frame feature or block matching correspondence. In the proposed technique, use of projection ensures accuracy under local perturbations, noise and blur conditions, while dual-accumulation eliminates the effect of dark-regions adding robustness to night-shooting condition. Efficiency of the proposed algorithm over the existing motion estimation techniques is tested and verified over different categories of night shooting videos. In addition to night video stabilization the proposed scheme also performs well under normal illumination.     

基于奇异值分解的图像目标跟踪算法

传统相关跟踪方法是利用模板图像与目标图像对应像素的灰度差异信息进行跟踪,它对旋转变化敏感,且存在跟踪累积误差,容易导致模板漂移而丢失目标。文中提出基于奇异值分解的跟踪算法,算法首先建立模板图像训练集合,利用奇异值分解方法,张成模板图像特征空间,然后求出模板图像在特征空间里的投影值,代替传统算法中灰度对两幅待匹配图像进行的全局搜索定位。在进行投影值间的相似性度量时,欧氏距离同等对待所有的特征向量不移合理,文中采用了一种鲁棒估计方法,可以对不同距离的值做不同处理。匹配跟踪实验效果良好。     

Global-motion estimation in image sequences of 3-D scenes for coding applications

A technique for global-motion estimation and compensation in image sequences of 3-D scenes is described in this paper. Each frame is segmented into regions whose motion can be described by a single set of parameters and a set of motion parameters is estimated for each segment. This is done using an iterative block-based image segmentation combined with the estimation of the parameters describing the global motion of each segment. The segmentation is done using a Gibbs-Markov model-based iterative technique for finding a local optimum solution to a maximum a posteriori probability (MAP) segmentation problem. The initial condition for this process is obtained by applying a Hough transform to the motion vectors of each block in the frame obtained by block matching. In each iteration, given a segmentation, the motion parameters are estimated using the least-squares (LS) technique. To obtain the final segmentation and the more appropriate higher-order motion model for each segment, a final stage of splitting/merging of segments is needed. This step is performed on the basis of maximum-likelihood decisions combined with the determination of the higher-order model parameters by LS. The incorporation of the proposed global-motion estimation technique in an image-sequence coder was found to bring about a substantial reduction in bit-rate without degrading the perceived quality or the PSNR.     

H.263甚低速率图像编码的全局判决实现方法

本文对Ｈ．２６３编码算法的现有实现方法作了深入的分析,首先发现变换部分存在大量无效运算,提出了在变换前加判决的前变换判决的编码方案,以压缩无效的变换运算;其次发现运动估计部分由于忽略了图像场景的分级运动而存在一定的无效搜索运算,提出了基于分级运动的可变搜索域法来压缩无效的搜索运算;最后将前变换判决方案与运动估计的可变搜索域法有机地结合在一起,提出了全局判决编码方案,从而比较全面地改进了现有实现方法,因而能大幅度地提高编码器的编码速度．