基于冗余小波变换的立体图像视差估计

通过分析目前立体视差估计方法的不足,提出一种基于冗余小波变换的视差估计新算法.首先对参考图像进行冗余小波变换,提取特征点,形成DT(Delaunay Triangle)网格,然后根据三角形特征点在目标图像中进行视差估计,最后通过仿射变换形成浓密视差图.实验表明该算法能有效获得视差矢量,视差匹配后能得到良好的重建图像.     

基于视差成像的多视点自由立体投影系统

人眼能获得立体视觉的根本原因是存在视差。利用柱面光栅能使投影成像在有限区域的特点，可以使人的双眼在同一时间分别看到不同的图像形成视差，从而获得立体视觉。本文提出一种双柱面结构的大屏幕自由立体背投系统，从理论上对其结构和成像原理进行了详细分析，并给出了计算机仿真结果。     

基于视差估计的中间视合成

提出了一种基于视觉估计的中间视合成方法.为了生成高质量的中间视图,在视差估计中提出了一种新的基于自适应权值的方法,并在匹配的代价函数中引入视差平滑性约束项.在获得可靠密集视差图后,通过寻找中间视图中像素点在左、右图像中的对应点来合成中间视.实验结果表明,本算法可以获得很好的视差图,合成的中间视图具有较高的质量.     

立体电视不同视差平面上的立体视锐度研究

通过生理感知试验,研究了双路立体电视不同视差平面上的立体视锐度.根据试验结果,人眼在0°视差平面上有最佳的立体视锐度,且随着画面中物体视差逐渐增大,人眼在观看该出/入屏物体时的立体视锐度将逐渐下降.此外,相比入屏物体而言,人眼在观看具有相同大小视差的出屏物体时具有更佳的立体视锐度.     

基于CCD的视度和视差测试系统研究

传统的光学系统对于视度及视差的测量通常采用平行光管视差仪或视度筒,其测量结果受人为主观因素影响较大.为满足望远系统测量视度及视差的精度要求;采用高分辨率CCD作为测量器件,经自动对焦和图像处理,由计算机直接给出测量结果,消除了人为因素影响,提高了测量准确度,操作简易.论述并推导了视度及视差的测试原理及计算公式,并对测试系统进行了误差分析.     

基于深度感知和主观评价的影响立体图像舒适度的视差范围研究

立体图像的视差很大程度上决定了立体图像的视觉舒适度,本文从定量的 角度对影响立体图 像舒适度的视差范围进行了研究。首先对源立体图像采用像素平移方法得到测试立体图像集 ,通过大量的 主观实验得到测试立体图像的舒适度平均意见得分(MOS,mean o pinion score)值;其次,基于视觉显著性特点,采用自适应权重立体匹配方 法计算各区域的视差值,以测试各区域视差值对整幅立体图像舒适度的影响程度;最后通过 转换公式将舒 适立体图像的视差范围转换为视差角形式,以便将本文方法推广到其他类型的显示设备。实 验结果表明, 在实验所用显示设备中,满足舒适要求的像素平移量为－40～90(左 移40pixels至右移90pixels);当 立体图像中心显 著区域的水平视差在－0.3882°～0.851范围内时, 其舒适度在可接受范围内,而视差范 围为－0.2713°～0.781时舒适度达到最佳;最后将本文方法推广到常用显示设备,并给出了常用显示设 备的舒适视差范围,为立体图像和视频的制作提供了可靠依据。     

基于视差补偿预测的立体视频图像压缩编码

本文介绍了立体视频编码方法,并对其关键技术-视差补偿预测技术进行深入研究.本文所提出的基于视差分割的视差补偿预测算法是建立在可变尺寸块匹配算法的基础上,充分利用视差信息实现对目标图像帧的有效分割,并采用相适应的视差向量编码方案.与传统算法相比,在相同预测精度下,明显降低了视差信息编码开销.     

基于引导滤波及视差图融合的立体匹配

立体匹配是双目视觉领域的重要研究方向.为在保证图片纹理区域匹配精度的同时降低弱纹理区域的误匹配率,提出一种基于引导滤波及视差图融合的立体匹配方法.首先,根据图像颜色相似性将图片划分为纹理较丰富区域和弱纹理区域.接着,分别采用不同参数的引导滤波进行代价聚合及视差计算,得到两张视差图.然后依据纹理区域划分的结果对获得的两张视差图进行融合.最后,通过左右一致性检测、加权中值滤波等视差优化步骤得到最终视差图.对Middlebury测试平台上标准图像对的实验结果表明,该方法在6组弱纹理图像上的平均误匹配率为9.67％,较传统引导滤波立体匹配算法具有更高的匹配精度.     

基于视差约束的3D立体视频重新定位研究

文中提出了一种视差约束的3D立体视频重新定位方法,该方法同时将双目视频调整为新的纵横比,并将深度感知进行重新映射。建立畸变能量建模来防止视频内的目标区域形变,通过模拟视差变化能量来约束空间域和时间域中的视差范围,实现了深度映射的稳定性。运用原始立体视频生成不同显示分辨率的高感知质量的图像版本,克服了能量模型中目标分辨率的非均匀性和像素形变的干扰。最后通过实验分析验证了所提方法的有效性。     

基于SIFT 匹配的多视点立体图像零视差调整

针对目标跟踪过程中目标可能出现的快速变化和严重遮挡等问题,提出了一种基于新的子空间表示的目标跟踪算法。采用距离不变量对尺度不变特征变换(SIFT)特征点匹配对进行提纯。用提纯后的特征点匹配对,通过线性拟合得到仿射变化参数。在粒子滤波的理论框架下,采用快速的迭代算法,建立目标的主分量(PCA)子空间表示,结合计算得到的仿射变化参数,构造有效的目标观测模型完成跟踪。同时,采用在线学习的方法对SIFT特征点和PCA子空间进行定时更新。大量实验表明,提出的算法能快速有效地完成对姿态和形状剧烈变化的目标的精确跟踪。     

User assisted disparity remapping for stereo images

This study concentrates on user assisted disparity remapping for stereo image footage, i.e. the disparity of an object of interest is altered while leaving the remaining scene unattended. This application is useful in the sense that it provides a method for emphasizing/de-emphasizing an object on the scene by adjusting its depth with respect to the camera. The proposed technique can also be used as a post-processing step for retargeting stereoscopic footage on different display sizes and resolutions. The proposed technique involves an MRF-based energy minimization step for interactive stereo image segmentation, for which user assistance on only one of the stereo pairs is required for determining the location of stereo object pair. A key contribution of the proposed study is elimination of dense disparity estimation step from the pipeline. This step is realized through a sparse feature matching technique between the stereo pairs. Moreover, by the help of the proposed technique, novel disparity adjusted views are synthesized using the produced stereo object segments and background information for the images. Qualitative and quantitative evaluation of the generated segments and the disparity adjusted images prove the functionality and superiority of the proposed technique.     

A new parallel hardware architecture for high-performance stereo matching calculation

In this paper, we propose a hardware (H/W) architecture to find disparities for stereo matching in real time. After analyzing the arithmetic characteristic of stereo matching, we propose a new calculating method that reuses the intermediate results to minimize the calculation load and memory access. From this, we propose a stereo matching calculation cell and a new H/W architecture. Finally, we propose a new stereo matching processor. The implemented H/W can operate at the clock frequency of 250 MHz at least in the FPGA (field programmable gate array) environment and produce about 120 disparity images per second for HD stereo images.     

Combining texture and stereo disparity cues for real-time face detection

Intuitively, integrating information from multiple visual cues, such as texture, stereo disparity, and image motion, should improve performance on perceptual tasks, such as object detection. On the other hand, the additional effort required to extract and represent information from additional cues may increase computational complexity. In this work, we show that using biologically inspired integrated representation of texture and stereo disparity information for a multi-view facial detection task leads to not only improved detection performance, but also reduced computational complexity. Disparity information enables us to filter out 90% of image locations as being less likely to contain faces. Performance is improved because the filtering rejects 32% of the false detections made by a similar monocular detector at the same recall rate. Despite the additional computation required to compute disparity information, our binocular detector takes only 42 ms to process a pair of 640×480 images, 35% of the time required by the monocular detector. We also show that this integrated detector is computationally more efficient than a detector with similar performance where texture and stereo information is processed separately.     

A new head pose tracking method based on stereo visual SLAM

Real-time and reliable head pose tracking is the basis of human–computer interaction and face analysis applications. Aiming at the problems of accuracy and real time performance in current tracking method, a new head pose tracking method based on stereo visual SLAM is proposed in this paper. The sparse head map is constructed based on ORB feature points extraction and stereo matching, then the 3D-2D matching relations between 3D mappoints and 2D feature points are obtained by projection matching. Finally, the camera pose solved by the Bundle Adjustment is converted to head pose, which realizes the tracking of head pose. The experimental results show that this method can obtain high precise head pose. The mean errors of three Euler angles are all less than 1°. Therefore, the proposed head pose tracking method can track and estimate precise head pose in real time under smooth background.     

一种新的体视对应方法

选择特征点作为匹配特征,采用视差估计方法,在满足一定匹配准则情况下,可以得到一约束最小化能量函数。模拟实验结果表明,使用模拟退火算法,可使能量函数达到全局最小,从而实现立体匹配。     

Stereo matching algorithm based on per pixel difference adjustment,iterative guided filter and graph segmentation

Stereo matching process is a difficult and challenging task due to many uncontrollable factors that affect the results. These factors include the radiometric variations and illumination inconsistence. The absolute differences (AD) algorithms work fast, but they are too sensitive to noise and low textured areas. Therefore, this paper proposes an improved algorithm to overcome these limitations. First, the proposed algorithm utilizes per-pixel difference adjustment for AD and gradient matching to reduce the radiometric distortions. Then, both differences are combined with census transform to reduce the effect of illumination variations. Second, a new approach of iterative guided filter is introduced at cost aggregation to preserve and improve the object boundaries. The undirected graph segmentation is used at the last stage in order to smoothen the low textured areas. The experimental results on the standard indoor and outdoor datasets show that the proposed algorithm produces smooth disparity maps and accurate results.     

Analysis of target tracking based on range difference measurement of multistatic radar system

An analysis is presented for target tracking with short range multistatic radar system in this paper. The velocity vector is introduced into the model to depict target motion more precisely. The system measurement equation is such constructed on the basis of range difference that make the tracking model independent of the transmitter position. Therefore the algorithm is very much suitable for the case that the transmitter is not fixed. Simulation results show that the algorithm has the advantages of fast tracking and small steady tracking errors, and can be used for tracking target in short range with multistatic radar system.     

Perceptual stereoscopic video coding using disparity just-noticeable-distortion model

In this paper, we propose perceptual stereoscopic video coding using a disparity just-noticeable-distortion (JND) model. We obtain the disparity JND model in stereo videos by disparity masking effects of the human visual system (HVS). The disparity JND model represents the maximum distortion of stereo perception that HVS cannot perceive. Based on the disparity JND model, we adjust prediction residuals to remove the perceptual redundancy of stereo videos. Thus, we achieve significant bit-rate saving while maintaining visual quality. Experimental results demonstrate that the proposed method significantly improves coding efficiency without loss of stereoscopic perceptual quality.     

Adaptive fractional motion and disparity estimation skipping in MV-HEVC

MV-HEVC can efficiently compress multiview video data captured from different viewpoints. To achieve high coding efficiency, it consists of not only inter coding but also interview coding. The inter coding includes a motion estimation (ME) process that reduces temporal redundancies between consecutive frames, and the interview coding performs a disparity estimation (DE) that reduces interview redundancies between neighboring views. As a result, MV-HEVC needs high encoding complexity to perform both ME and DE. In order to reduce the complexity, this paper proposes an adaptive fractional ME and DE skipping method in a partitioned inter prediction unit (PU) mode, based on a result of a 2 N × 2 N inter PU coding. Experimental results show that the proposed method efficiently reduces the encoding complexity with negligible coding loss, compared to conventional methods.     

Discontinuity preserving disparity estimation with occlusion handling

In this paper, we propose a stereo matching algorithm based on distance transform to generate high-quality disparity maps with occlusion handling. In general, pixel intensities around object edges are smeared due to mixed values located between the object and its background. This leads to problems when identifying discontinuous disparities. In order to handle these problems, we present an edge control function according to distance transform values. Meanwhile, occluded regions occur, i.e., some portions are visible only in one image. An energy function is designed to detect such regions considering warping, cross check, and luminance difference constraints. Consequently, we replace the disparity in the occluded region with the one chosen from its neighboring disparities in the non-occluded region based on color and spatial correlations. In particular, the occlusion hole is filled according to region types. Experimental results show that the proposed method outperforms conventional stereo matching algorithms with occlusion handling.