动态场景视频序列中的前景区域自动提取

首先提出一种具有自适应外点过滤功能的全局运动估计算法,通过交替地进行参数估计和外点过滤,能够有效地抑制噪声的影响,实现准确的背景对准;然后,通过直方图拟合获得准确的背景噪声方差值,克服了以往只能依据经验设定背景噪声方差的缺点,并使用显著性测试技术有效地对帧差图进行二值化,最终消除帧间的重叠背景,提取出前景区域．实验结果表明,该算法能够有效地实现动态场景视频序列中的背景对准,并准确地提取出前景区域．     

基于运动矢量分量差的视频隐写算法

针对H.264/AVC视频压缩标准,提出基于运动矢量分量差的隐写算法。根据人眼视觉特性,筛选出人眼较不敏感的运动矢量,计算其分量差以控制嵌入操作的位置,并在选定的运动矢量分量中嵌入秘密信息。由于操作具有对称性,因此对视频质量的影响较小。理论分析和实验结果证明,该算法具有较高的载体利用率和嵌入效率,能够达到视频隐蔽通信对隐蔽性和隐写容量的要求。     

Hierarchical Estimation and Segmentation of Dense Motion Fields

In this paper we present a comprehensive energy-based framework for the estimation and the segmentation of the apparent motion in image sequences. The robust cost functions and the associated hierarchical minimization techniques that we propose mix efficiently non-parametric (dense) representations, local interacting parametric representations, and global non-interacting parametric representations related to a partition into regions. Experimental comparisons, both on synthetic and real images, demonstrate the merit of the approach on different types of photometric and kinematic contents ranging from moving rigid objects to moving fluids.     

H.263+视频编码器中运动估计搜索算法的选择

对常用的运动估计搜索算法原理进行了分析，并在H．263＋测试模型上对各种算法的性能进行了测试。通过对测试数据的比较，基于中心的三步搜索法（CTSS）具有搜索精度高，速度快的优点，可作为H．263＋视频编码器的运动估计算法。     

Stochastic Approximation and Rate-Distortion Analysis for Robust Structure and Motion Estimation

Recent research on structure and motion recovery has focused on issues related to sensitivity and robustness of existing techniques. One possible reason is that in practical applications, the underlying assumptions made by existing algorithms are often violated. In this paper, we propose a framework for 3D reconstruction from short monocular video sequences taking into account the statistical errors in reconstruction algorithms. Detailed error analysis is especially important for this problem because the motion between pairs of frames is small and slight perturbations in its estimates can lead to large errors in 3D reconstruction. We focus on the following issues: physical sources of errors, their experimental and theoretical analysis, robust estimation techniques and measures for characterizing the quality of the final reconstruction. We derive a precise relationship between the error in the reconstruction and the error in the image correspondences. The error analysis is used to design a robust, recursive multi-frame fusion algorithm using stochastic approximation as the framework since it is capable of dealing with incomplete information about errors in observations. Rate-distortion analysis is proposed for evaluating the quality of the final reconstruction as a function of the number of frames and the error in the image correspondences. Finally, to demonstrate the effectiveness of the algorithm, examples of depth reconstruction are shown for different video sequences.     

基于多分辨率四叉树的运动分割及交叠块的立体视频帧估计算法

为了对立体视频序列进行有效的编解码，以获得较好的重建图象，提出了一种基于立体视频序列的帧估计及内插方法，该方法就是在立体视频序列编码中，左图象流按MPEG－Ⅰ/Ⅱ的视频编码标准进行编码；面对右图象流，只对参考帧（Ⅰ帧及P帧）进行编码，右图象流的B帧不进行编码及传送，而是在解码端，根据各个参考帧通过帧及内插来获得，可变块分割的方法是采用基于多分辨率四叉树分解的运行分割，对右B帧的重建按照匹配块和失配块分别处理的方法，各个块的位置和内容则根据右B帧中的块与右Ⅰ帧、P帧之间或与左B帧的之间相关性大小来确定，另外，还提出了一种新的可避免误区配和对显露区进行正确填充，并针对交叠块的帧估计和内插方法，仿真实验表明，该图象重建方法与文献[1]所提出的基于固定块的方法相比，能够使得重建图象的峰值信噪比（PSNR）增加约1.25dB，并且图象的主观视觉质量评价也明显要好。     

基于数学形态学的运动估计及VLSI设计

提出的基于数学形态学的运动估计算法,采用四场的SAD比较进行运动估计,并且对运动向量进行数学形态学滤波处理(先进行腐蚀,再进行扩散处理),削弱噪声影响,提高运动估计的精度.在VLSI实现中采用外挂SDRAM作为帧存储器,存储前两场图像数据和运动信息.本算法和VLSI设计经过FPGA验证,取得了很好的效果,并且已经被成功地应用于基于SMIC 0.18 μm CMOS工艺的数字视频处理芯片中.     

Open Divx视频编码程序的并行性分析与优化研究

Open Divx是一种基于MPEG-4思想开发的视频压缩软件。为了解决嵌入式条件下视频数据的实时压缩问题，本文对Open Divx视频编码程序进行了循环级并行性和指令级并行性的分析。最后，我们得出了Open Divx视频编码程序更适合于在采用多整数运算功能部件的体系结构环境下运行的结论。     

H.266/VVC中一种改进的仿射运动估计算法

通用视频编码标准H.266/VVC通过引入多种新的编码技术,如仿射运动补偿预测、自适应运动矢量精度、多核变换等,以支持360°视频和HDR视频的编解码,从而为用户提供最优的视频质量,但是在H.266/VVC帧间预测过程中,仿射运动估计计算复杂度高导致编码时间显著增加。针对该问题,提出一种改进的仿射运动估计算法。通过对仿射高级矢量预测（AAMVP）候选列表的构建过程进行改进,并构建一种AAMVP候选列表候选项筛选准则,使得列表的候选项更接近编码块真实的运动矢量,从而缩短编码时间。同时对仿射运动估计中迭代搜索最优仿射运动矢量的迭代过程进行优化,以加快迭代搜索速度。实验结果表明,在低时延的编码器配置下,相比VVC原始算法,当BD-BR增加了0.023%时,该算法的总体编码时间平均缩短13%,在保证编码质量的前提下能够有效降低编码的计算复杂度。     

运动辅助的CPG控制及其关键参数分析

针对运动辅助过程中主/从运动生成的问题,在原有松岗（Matsuoka）数学模型的基础上引入适应系数建立了一个新的CPG模型,获得了理想的主/从关节目标轨迹;利用仿真分析手段调查研究了CPG模型的关键参数对其输出振荡的影响规律;以单关节运动辅助为控制对象,建立了相应的人机交互运动系统的动力学模型,利用基于MATLAB的仿真试验对CPG控制的有效性进行了验证。结果表明,根据CPG各个参数与输出的变化规律,适当调节各个参数可以获得理想的输出;CPG生成的运动轨迹有效规避了传统助力机器人控制模型中复杂的运动学和动力学解算;可根据实际需求调整外部参数[C]从而有效地生成辅助装置主/从运动模式;控制方法对单关节运动辅助具有明显效果。     

Visual Analysis of Spatio‐Temporal Data: Applications in Weather Forecasting

Weather conditions affect multiple aspects of human life such as economy, safety, security, and social activities. For this reason, weather forecast plays a major role in society. Currently weather forecasts are based on Numerical Weather Prediction (NWP) models that generate a representation of the atmospheric flow. Interactive visualization of geo‐spatial data has been widely used in order to facilitate the analysis of NWP models. This paper presents a visualization system for the analysis of spatio‐temporal patterns in short‐term weather forecasts. For this purpose, we provide an interactive visualization interface that guides users from simple visual overviews to more advanced visualization techniques. Our solution presents multiple views that include a timeline with geo‐referenced maps, an integrated webmap view, a forecast operation tool, a curve‐pattern selector, spatial filters, and a linked meteogram. Two key contributions of this work are the timeline with geo‐referenced maps and the curve‐pattern selector. The latter provides novel functionality that allows users to specify and search for meaningful patterns in the data. The visual interface of our solution allows users to detect both possible weather trends and errors in the weather forecast model. We illustrate the usage of our solution with a series of case studies that were designed and validated in collaboration with domain experts.     

Color spectral analysis for spatial structure characterization of textures in IHLS color space

In this article, a linear prediction model based approach for color texture characterization and classification in the improved hue luminance and saturation color space is presented. Pure chrominance structure information is used in addition to the normally used luminance structure information for color texture classification. Hue and saturation channels of a color image in IHLS color space are combined using a complex exponential to give a single channel which holds all the chrominance information of the image. Two dimensional complex multichannel versions of the non-symmetric half plane autoregressive model, the quarter plane autoregressive model and the Gauss Markov random field model are used to perform parametric power spectrum estimation of both luminance and the “combined chrominance” channels of the image. The accuracy and precision of these spectral estimates are proven quantitatively by performing tests on a large number of images. Spectral distance measures are calculated for the spectral information of luminance and chrominance channels individually as well as combined through a combination coefficient. Using these distance measures, color texture classification is done with k-nearest neighbor algorithm. Experimental results verify that the IHLS color space exhibits better performance than the RGB color space indicating the significance of using IHLS for such analysis. They also show that color texture characterization and percentage classification obtained by combined luminance and chrominance structure information is better than the color texture classification done using only the luminance structure information.