Error concealment for shape in MPEG-4 object-based video coding.

In asynchronus transfer mode networks, cell loss or channel errors can cause data to be dropped in the channel. When digital images/videos are transmitted over these networks, one must be able to reconstruct the missing data so that the impact of the errors is minimized. In this paper, we present an error-concealment technique for shape in MPEG-4 object-based video coding. This method, which is based on using global motion estimation and compensation techniques for boundary recovery, consists of three steps: (1) boundary extraction from shape; (2) boundary patching using global motion compensation; and (3) boundary filling to reconstruct the shape of the damaged video object planes. Global motion parameters are inserted as part of the USER_DATA field in the compressed stream and are utilized in reconstructing the damaged boundaries of compressed video object planes.     

基于三维小波变换嵌入式视频压缩算法的研究

本文把二维图像的等级树集分割编码方法(SPIHT)推广应用于三维的视频编码中,提出了一种用于三维视频序列图像的扩展等级树集分割编码方法.此方法所编码码流是嵌入式码流,在解码端可随意截取一段码流解码以达到所要求的码率和视频质量.另外此方法无需进行运动补偿,降低了算法的复杂度.通过理论分析和仿真实验得出,此方法有很好的编码效率,但对于帧内图像较复杂的序列,编码效率有所下降.     

基于运动补偿的自适应时域视频降噪算法研究

视频信号内的噪声是信号中不希望出现的干扰部分,如果不加以有效的去除,会严重影响视频图像的质量.提出了一种基于运动补偿的自适应时域视频降噪算法.该方法通过运动补偿技术,在时域上跟踪并提取噪声.滤波的强度是根据物体运动轨迹上的运动强度自适应变化的.利用该算法,有效地去除了视频序列中的噪声,同时很好地保护了图像的细节.实验结果表明,采用该降噪算法处理后的视频图像质量明显优于采用空域的降噪方法的结果.     

基于OpenCV的动态背景下的运动目标检测

研究在动态背景下对视频图像序列进行运动目标的检测。主要包括三个步骤,分别是运动估计,运动补偿和目标检测。在运动估计中采用的主要是基于特征点匹配算法。这种算法与传统的块匹配算法最大的好处在于它的数据量少,计算简单迅速而且图像的匹配可靠性更高。最后用计算机视觉库OpenCV进行实现。     

Segmentation and tracking of moving objects for content-based videocoding

To enable content-based functionalities in video coding, a decomposition of the scene into physical objects is required. Such objects are normally not characterised by homogeneous colour, intensity, or optical flow. Therefore, conventional techniques based on these low-level features cannot perform the desired segmentation. The authors address segmentation and tracking of moving objects and present a new video object plane (VOP) segmentation algorithm that extracts semantically meaningful objects. A morphological motion filter detects physical objects by identifying areas that are moving differently from the background. A new filter criterion is introduced that measures the deviation of the estimated local motion from the synthesised global motion. A two-dimensional binary model is derived for the object of interest and tracked throughout the sequence by a Hausdorff object tracker. To accommodate for rotations and changes in shape, the model is updated every frame by a two-stage method that accounts for rigid and non-rigid moving parts of the object. The binary model then guides the actual VOP extraction, whereby a novel boundary post-processor ensures high boundary accuracy. Experimental results demonstrate the performance of the proposed algorithm     

分布式视频编码中的边信息优化算法*

在分布式视频编码中的运动补偿插值算法通常采用正方形分块方案,然而考虑到视频中物体的运动和复杂的图像纹理结构,仅采用正方形分块不能得到优异的匹配效果.因此在基于小波域的分布式视频编码系统基础上,采用非规则分块方案来提取物体的边缘信息,从而提高运动估计时的匹配精度.实验结果表明,该方案在一定程度上能提高边信息质量.     

Three-dimensional modeling from two-dimensional video

This paper presents the surface-based factorization method to recover three-dimensional (3-D) structure, i.e., the 3-D shape and 3-D motion, of a rigid object from a two-dimensional (2-D) video sequence. The main ingredients of our approach are as follows: 1) we describe the unknown shape of the 3-D rigid object by polynomial patches; 2) projections of these patches in the image plane move according to parametric 2-D motion models; 3) we recover the parameters describing the 3-D shape and 3-D motion from the 2-D motion parameters by factorizing a matrix that is rank 1 in a noiseless situation. Our method is simultaneously an extension and a simplification of the original factorization method of Tomasi and Kanade (1992). We track regions where the 2-D motion in the image plane is described by a single set of parameters, avoiding the need to track a large number of pointwise features, in general, a difficult task. Then our method estimates the parameters describing the 3-D structure by factoring a rank 1 matrix, not rank 3 as in Tomasi and Kanade. This allows the use of fast iterative algorithms to compute the 3-D structure that best fits the data. Experimental results with real-life video sequences illustrate the good performance of our approach     

An effective mesh-based motion compensation technique for video coding

The block-matching algorithm is the most popular motion compensation technique in video coding. However, it cannot provide acceptable quality at very low bit rate. In this paper, a new mesh-based motion compensation method is proposed to attack the problem. First, a regular non-uniform mesh, which has regular structure with variable patch size, is presented. The patch size is varied according to motion activity of a video sequence. Next, a weighted interpolation block matching is developed to improve the estimate accuracy of displacements of grid points. It utilizes the motion correlation between a grid point and its associated patches. Finally, based on the new mesh and motion estimation scheme, an efficient motion compensation algorithm is developed. When compared to the conventional motion compensation techniques, the proposed method improves performance significantly with lower computational complexity and overhead information bits.     

Neural fuzzy motion estimation and compensation

Neural fuzzy systems can improve motion estimation and compensation for video compression. Motion estimation and compensation are key parts of video compression. They help remove temporal redundancies in images. But most motion estimation algorithms neglect the strong temporal correlations of the motion field. The search windows stay the same through the image sequences and the estimation needs heavy computation. A neural vector quantizer system can use the temporal correlation of the motion field to estimate the motion vectors. First- and second-order statistics of the motion vectors give ellipsoidal search windows. This algorithm reduced the search area and entropy and gave clustered motion fields. Motion-compensated video coding further assumes that each block of pixels moves with uniform translational motion. This often does not hold and can produce block artifacts. We use a neural fuzzy system to compensate for the overlapped block motion. This fuzzy system uses the motion vectors of neighboring blocks to map the prior frame's pixel values to the current pixel value. The neural fuzzy system used 196 rules that came from the prior decoded frame. The fuzzy system learns and updates its rules as it decodes the image. The fuzzy system also improved the compensation accuracy. The paper derives both the fuzzy system and the neural learning laws that tune its parameters     

MPEG-4自然视频编码技术

对MPEG－4自然视频编码的关键技术作了详细的分析和阐述。首先介绍MPEG－4频语法结构，并对视频编码的框架概要分析。接着分析了自然视频编码中涉及到的关键技术，包括：VOP的产生；二值和灰度级α平面的编码技术；运动估计和补偿方法；纹理编码；基于对象的时间分级和空间分级；MPEG－4提供的再同步和各种错误掩盖，刷新方法，精 编码技术和零树小波基的静止图像编码技术。指出MPEG－4和MPEG－1，MPEG－2等标准的异同，突出MPEG－4的三个主要特点。最后给出MPEG－4技术在网络视频传输中的应用，并给出测试和分析。     

Automatic scalable face model design for 2D model-based video coding

Scalable low bit-rate video coding is vital for the transmission of video signals over wireless channels. A scalable model-based video coding scheme is proposed in this paper to achieve this. This paper mainly addresses automatic scalable face model design. Firstly, a robust and adaptive face segmentation method is proposed, which is based on piecewise skin-colour distributions. 43 million skin pixels from 900 images are used to train the skin-colour model, which can identify skin-colour pixels reliably under different lighting conditions. Next, reliable algorithms are proposed for detecting the eyes, mouth and chin that are used to verify the face candidatures. Then, based on the detected facial features and human face muscular distributions, a heuristic scalable face model is designed to represent the rigid and non-rigid motion of head and facial features. A novel motion estimation algorithm is proposed to estimate the object model motion hierarchically. Experimental results are provided to illustrate the performance of the proposed algorithms for facial feature detection and the accuracy of the designed scalable face model for representing face motion.     

基于运动矢量场的运动目标区域检测

基于稀疏运动矢量场,提出一种动态背景下的运动 目标区域检测方法。根据运动矢量场特性分析进行全局运动 参数估计和全局运动补偿,实现动态场景中的背景校正;利用最大树数据结构, 基于运动矢量补偿误差分级表示视频帧中 运动基本一致的连通区域,进行运动区域初始分类;根据运动目标在空间上的连通性和运动 一致性的特点,选择区域相似性 度量准则,进行区域合并和滤波,将具有相似运动的连通区域合并,实现运动目标区域检测 。将检测出的运动目标区域作为 运动矢量外点反过来又应用于全局运动参数估计过程中,全局运动估计和运动目标区域检测 交替地进行,不仅加快了它们的 计算速度,同时也提高了它们计算和检测的准确性。实验结果表明,本文算法能较好地补偿 序列的全局运动,有效地检测出 局部目标运动区域。     

Contour simplification and motion compensated coding

In order to solve the bottleneck problem of region-based coding scheme, which is the contour coding, lossy methods are introduced in this paper for both 2D and 3D (2D plus time) contour image(s). A non-linear filter by means of majority operation is designed to act as contour simplification for both pre-processing and post-processing of contour coding. An average of 20% gain in contour coding cost is achieved by using this filter while the contour location error is controlled within one pixel width. Afterwards, an efficient contour motion estimation and compensated coding method are presented. In order to exploit the high temporal redundancy of the contour image sequence, motion estimation and compensation are applied to the correspondent label image sequence. First frame is directly coded by Chain-code method. All the following frames are coded in motion compensated mode. Meanwhile, a fast implementation of full search motion estimation algorithm is also described. This algorithm is 2R times faster than traditional method (R is the total regional number). Within each frame, labels are divided into foreground labels and background labels. Only the noticeable prediction errors for the foreground labels are coded. Morphological filters are used to clean the prediction errors of the foreground labels. An efficient prediction error coding algorithm is then introduced based on one-side Chain-code method. The reconstruction of foreground and background regions in the decoder side is also described. Experimental results have demonstrated good performance for very low bitrate video coding applications.     

Wavelet-based very low bit-rate video coding using image warpingand overlapped block motion compensation

The authors present an algorithm for very low bit-rate video coding that combines new ideas in motion estimation, wavelet filter design, and wavelet-based coding techniques. A new motion compensation technique using image warping and overlapped block motion compensation is proposed to reduce temporal redundancies in a given image sequence. This combined motion model has the advantage of representing more complex motion than simple block matching schemes. To further improve the quality of the temporal prediction, an adaptive grid with variable density according to the varying motion activity of a given scene is generated. An adaptively switched high-quality texture interpolation is employed to cope with the problem of fractional displacements in such a way that both objective and subjective reconstruction quality is improved. Spatial decorrelation of the motion compensated residual images is performed using an one-parametric family of biorthogonal infinite impulse response (IIR) wavelet filters coupled with the highly efficient pre-coding scheme of `partitioning, aggregation and conditional coding' (PACC). Experimental results demonstrate significant improvements in objective quality of 1.0-2.3 dB PSNR in comparison to the H.263+ test model TMN10 using advanced coding options. In addition, the authors' intracoding method provides a performance gain of 0.5 dB PSNR on the average for a test suite of various still images when compared to the emerging still image coding standard JPEG-2000     

Optimization of quadtree segmentation and hybrid two-dimensionaland three-dimensional motion estimation in a rate-distortion framework

A rate-distortion framework is used to define a very low bit-rate coding scheme based on quadtree segmentation and optimized selection of motion estimators. This technique achieves maximum reconstructed image quality under the constraint of a target bit rate for the coding of the vector field and segmentation information. First, a complete scheme is proposed for hybrid two-dimensional (2-D) and three-dimensional (3-D) motion estimation and compensation. The quadtree object segmentation is optimized for hybrid motion estimation in the rate-distortion sense. This scheme adapts to the depth of the quadtree and the technique used for motion estimation for each leaf of the tree. A more sophisticated technique, adapted to the requirements of a very low bit-rate coder, is also proposed which also considers the transmission of the prediction error corresponding to the particular choice of the motion estimator. Based on these coding schemes, two versions of a very low bit-rate image sequence coder are developed. Experimental results illustrating the performance of the proposed techniques in very low bit-rate image sequence coding application areas are presented and evaluated     

一种基于运动对象的形状编码新算法

本文提出一种基于运动对象的形状编码新方法,称之为基于曲率尺度空间CSS(Curvature Scale Space)的自适应算术形状编码算法(CSSAS).本算法主要分为两种编码模式:帧内模式和帧间模式.在帧内模式中,我们在对CSS算法进行改进的基础上,对任意形状对象的形状信息进行特征点的分层提取;并用自适应算术编码算法对提取的特征点进行编码.在帧间模式中,提出了一种基于曲率尺度空间图(CSSI)的任意形状对象的运动估计算法.上述运动估计/补偿后所获得的形状曲线的匹配部分使用基于弧长索引的压缩编码算法,而对于不匹配部分,采用与帧内CSSAS算法相同的方法进行压缩编码.实验结果表明,本文提出的CSSAS算法与MPEG-4校验模型中基于上下文的算术形状编码算法(CAE)相比,在帧内模式时,CSSAS比CAE压缩比提高约25%,在帧间模式Dn较大时,CSSAS比CAE压缩比明显提高,而在重构形状的主观质量上,CSSAS这两种模式均优于CAE.     

3D structure extraction coding of image sequences

This paper presents a 3D structure extraction coding scheme that first computes the 3D structural properties such as 3D shape, motion, and location of objects and then codes image sequences by utilizing such 3D information. The goal is to achieve efficient and flexible coding while still avoiding the visual distortions through the use of 3D scene characteristics inherent in image sequences. To accomplish this, we present two multiframe algorithms for the robust estimation of such 3D structural properties, one from motion and one from stereo. The approach taken in these algorithms is to successively estimate 3D information from a longer sequence for a significant reduction in error. Three variations of 3D structure extraction coding are then presented — 3D motion interpolative coding, 3D motion compensation coding, and “viewpoint” compensation stereo image coding — to suggest that the approach can be viable for high-quality visual communications.     

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。     

应用Virtual SPECK的视频编码技术

讨论并实现了基于提升格式三维小波变换的Virtual SPECK视频编码方法。该方法不涉及运动估计和运动补偿，具有计算量较小、编码快、低复杂的特点，产生的视频流是完全嵌入的。实验结果表明该方法能够快速的高效的压缩视频图像，是一种很有潜力的视频压缩编码方法。