Stereo image analysis for multi-viewpoint telepresence applications

An improved method for combined motion and disparity estimation in stereo sequences to synthesize temporally and perspectively intermediate views is presented. The main problems of matching methods for motion and disparity analysis are summarised. The improved concept is based on a modified block matching algorithm in which a cost function consisting of feature- and area-based correlation together with an appropriately weighted temporal smoothness term is applied. Considerable improvements have been obtained with respect to the motion and disparity assignments by introducing a confidence measure to evaluate the reliability of estimated correspondences. In occluded image areas, enhanced results are obtained applying an edge-assisted vector interpolation strategy. Two different image synthesis concepts are presented. The first concept is suitable for processing natural stereo sequences. It comprises the detection of covered and uncovered image areas caused by motion or disparity. This information is used to switch between different interpolation and extrapolation modes during the computation of intermediate views. The proposed object-based approach is suitable for processing typical video conference scenes containing extremely large occluded image regions and keeping implementation costs low. A set of stereo sequences has been processed. The performed computer simulations show that a continuous motion parallax can be obtained with good image quality by using sequences taken with stereo cameras having large interaxial distances.     

Fast synthesized and predicted just noticeable distortion maps for perceptual multiview video coding

The just noticeable distortion (JND) map is a useful tool for perceptual video coding. However, direct calculation of the JND map incurs high complexity, and the problem is aggravated in multiview video coding. In this paper, two fast methods are proposed to generate the JND maps of multiview videos. In the first method, the JND maps of some anchor views are used to synthesize the JND maps of other views via the depth image based rendering (DIBR), which can be much faster than direct JND computation. In the second method, the motion and disparity vectors obtained during the video coding are employed to predict the JND maps. If the prediction is not satisfactory, the JND block will be refreshed by calculating the JND directly. This method does not need any camera parameters and depth maps. The performances of the two fast JND map generation methods are evaluated in a perceptual MVC framework, where the residuals after spatial, temporal, or inter-view prediction are tuned according to the JND thresholds to save the bits without affecting the perceptual quality. Experimental results show that the JND prediction method has better accuracy and lower complexity. In addition, both fast JND methods lead to negligible degradation of the coding performance, compared to the direct JND method.     

Rigid and non-rigid 3D motion estimation from multiview image sequences

Multiview image sequence processing has been the focus of considerable attention in recent literature. This paper presents an efficient technique for object-based rigid and non-rigid 3D motion estimation, applicable to problems occurring in multiview image sequence coding applications. More specifically, a neural network is formed for the estimation of the rigid 3D motion of each object in the scene, using initially estimated 2D motion vectors corresponding to each camera view. Non-linear error minimization techniques are adopted for neural network weight update. Furthermore, a novel technique is also proposed for the estimation of the local non-rigid deformations, based on the multiview camera geometry. Experimental results using both stereoscopic and trinocular camera setups illustrate and evaluate the proposed scheme.     

A mesh-based disparity representation method for view interpolation and stereo image compression.

This paper proposes a mesh-based representation method for the disparity map of stereo images. The proposed method is designed to concentrate mainly on applications of view interpolation and stereo image compression. To obtain high image quality in the view interpolation and compression of stereo images, we formulate the view-interpolation error and prediction error. In the formulation, the view-interpolation and prediction errors depend not only on the accuracy of the disparity map, but also on the gradient of the stereo images. The proposed representation method for the disparity map is based on a triangular mesh structure, which minimizes the formulated interpolation and prediction errors. The experimental results show that the proposed method yields higher quality view-interpolated images and also has better performance in stereo image compression than the conventional methods.     

Efficient depth map generation with occlusion handling for various camera arrays

In this paper, we propose a direct depth map acquisition method for the arc camera array as well as the parallel camera array. In conventional stereo matching algorithms, image rectification is necessary where disparity values are obtained by identifying correspondences in the identical horizontal line of stereo images. The acquired disparity values are then transformed to depth values. However, image rectification may fabricate unwanted outcomes related to the arc camera array. Thus, the proposed method excludes image rectification and directly extracts depth values using an epipolar constraint. In particular, occlusion detection and handling processes are inserted to increase depth map accuracy. Further, belief propagation-based energy optimization is employed to confirm occlusion regions. Then, reasonable depth values are assigned to obtained occlusion regions using distances and color differences of neighbor pixels. Experimental results show that compared to the conventional methods, the proposed method generate more stable depth maps with fewer limitations.     

基于差异的视差估计方法研究

视差估计在立体图像编码、视频检索、立体图像分割等领域有重要的应用,是进行图像、视频分析的基础。首先,基于模糊隶属度提出了一种基于差异的视差估计方法;其次,引入模糊隶属度,把图像灰度转换为差异值;然后,分析了多块匹配的优越性;提出了基于多块匹配的视差估计方法;最后,在Middlebury网站上的测试结果证明了该方法的有效性。     

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.     

一种利用MAP估计的双目运动体视算法

本文提出一种融合运动和体视信息的运动与结构参数的鲁棒估计算法，算法首先通过计算瞬时ＦＯＥ，实现对每个像素处位移的ＭＡＰ估计，并计算关联的置信度；然后利用位移估计，从两图像序列之一计算相对深度，导出能用于匹配两体视图像序列的视差先验概率分布，使体视对的两帧图像匹配，确定３Ｄ景物深度，算法可方便地估计每个像素处的视差，不需对表面作平滑假设。     

Edge-preserving disparity estimation and disparity-compensated intermediate view reconstruction for stereo images

A constrained disparity estimation method is proposed which uses a directional regularization technique to efficiently preserve edges for stereo image coding. The proposed method smoothes disparity vectors in smooth regions and preserves edges in object boundaries well, without creating an oversmoothing problem. The differential pulse code modulation (DPCM) technique for disparity map coding is used prior to entropy coding, in order to improve the overall coding efficiency. The proposed disparity estimation method can also be applied to intermediate view reconstruction. Intermediate views between a left image and a right image provide reality and natural motion parallax to multiviewers. Intermediate views are synthesized by appropriately exploiting an interpolation or an extrapolation technique according to the characteristics of each region after identifying the regions as occluded regions, normal regions, and regions having ambiguous disparities.The experimental results show that the proposed disparity estimation method gives close matches between a left image and a right image and improves coding efficiency. In addition, we can subjectively confirm that the application of our proposed intermediate view reconstruction method leads to satisfactory intermediate views from a stereo image pair.This work was supported by the Korea Institute of Science and Technology (KIST) under Grant No. 99HI-054.     

Hole‐Filling Methods Using Depth and Color Information for Generating Multiview Images

This paper presents new hole‐filling methods for generating multiview images by using depth image based rendering (DIBR). Holes appear in a depth image captured from 3D sensors and in the multiview images rendered by DIBR. The holes are often found around the background regions of the images because the background is prone to occlusions by the foreground objects. Background‐oriented priority and gradient‐oriented priority are also introduced to find the order of hole‐filling after the DIBR process. In addition, to obtain a sample to fill the hole region, we propose the fusing of depth and color information to obtain a weighted sum of two patches for the depth (or rendered depth) images and a new distance measure to find the best‐matched patch for the rendered color images. The conventional method produces jagged edges and a blurry phenomenon in the final results, whereas the proposed method can minimize them, which is quite important for high fidelity in stereo imaging. The experimental results show that, by reducing these errors, the proposed methods can significantly improve the hole‐filling quality in the multiview images generated.     

Vector Lifting Schemes for Stereo Image Coding

Many research efforts have been devoted to the improvement of stereo image coding techniques for storage or transmission. In this paper, we are mainly interested in lossy-to-lossless coding schemes for stereo images allowing progressive reconstruction. The most commonly used approaches for stereo compression are based on disparity compensation techniques. The basic principle involved in this technique first consists of estimating the disparity map. Then, one image is considered as a reference and the other is predicted in order to generate a residual image. In this paper, we propose a novel approach, based on vector lifting schemes (VLS), which offers the advantage of generating two compact multiresolution representations of the left and the right views. We present two versions of this new scheme. A theoretical analysis of the performance of the considered VLS is also conducted. Experimental results indicate a significant improvement using the proposed structures compared with conventional methods.     

立体视频图像编码的研究进展

从编码方案、关键技术和评价准则3个方面综述了立体视频图像编码研究的发展.阐明了各种编码方案的特点及适用范围.详细分析了立体视频图像编码中视差估计、运动估计、遮挡检测、残差图像编码和码率控制5大关键技术,总结了各项技术的发展现状.最后指出了立体视频图像编码研究中存在的问题,并对未来的研究方向进行了展望.     

Joint Motion and Disparity Fields Estimation for Stereoscopic Video Sequences

In this paper, we present a separate edge-preserving regularization scheme to calculate disparity fields for a stereoscopic image pair and a joint disparity and motion estimation algorithm for stereoscopic video sequences. We aim at using the block-based joint estimation algorithm to calculate the displacement fields for stereoscopic and multiview video coding. In the proposed separate regularization scheme, an edge-preserving cost function is proposed for matching, the Sobel edge values are incorporated into the cost function as edge-preserving weights. The optimal Lagrange multiplier is determined using the convex hull bisection algorithm under the rate-distortion theory. A fast algorithm is then proposed where the textured regions and the homogeneous regions of the images are identified and regularized differently. In the joint regularization scheme, we calculate the two motion fields and the two disparity fields for two successive image pairs simultaneously. The four fields are regularized iteratively under the stereo-motion consistency constraint. Results are compared with existing algorithms and the superior performance of the proposed methods is confirmed.     

一种基于立体视邻接帧时空相关性的最小代价函数帧估计算法

为了在立体视频序列编码中获得高的压缩率,需要对立体视频序列中一个视的序列按传统方法进行独立编码;另一个视的序列中,只对其中一些参考帧(I帧或P帧)按视差补偿预测的方法进行编码,其余帧不进行编码和传输,而在解码端用立体视帧估计的方法得到重建.本文提出了一种基于立体视中邻接帧在图像、视差场和运动矢量场之间高度相关性的方法.对于因遮挡而缺乏估计的区域,则结合了图像强度的连续性和运动,视差矢量的分布特性,构造了代价方程并估计出该部分的运动矢量及强度值.实验证明,重建出来的帧图像在视觉和信噪比意义上均具有较好的效果.     

Stereoscopic ranging by matching image modulations

We apply an AM-FM surface albedo model to analyze the projection of surface patterns viewed through a binocular camera system. This is used to support the use of modulation-based stereo matching where local image phase is used to compute stereo disparities. The local image phase is an advantageous feature for image matching, since the problem of computing disparities reduces to identifying local phase shifts between the stereoscopic image data. Local phase shifts, however, are problematic at high frequencies due to phase wrapping when disparities exceed +/-pi. We meld powerful multichannel Gabor image demodulation techniques for multiscale (coarse-to-fine) computation of local image phase with a disparity channel model for depth computation. The resulting framework unifies phase-based matching approaches with AM-FM surface/image models. We demonstrate the concepts in a stereo algorithm that generates a dense, accurate disparity map without the problems associated with phase wrapping.     

Multi-View Video Coding Based on Vector Estimation and Weighted Disparity Interpolation

Aiming at fully exploiting the temporal and spatial redundancy and answering the “Call for Proposals” for multi-view video coding (MVC) issued by MPEG, a MVC scheme based on vector field estimation and weighted disparity interpolation is presented. By extending the loop constraint to multi-view images for a parallel camera model and proposing the novel “vector field estimation” scheme, the temporal and spatial redundancy is significantly reduced. Also, weighted disparity interpolation is performed to predict adjacent disparity vectors. Experimental results over multi-view image sets imply that the coding efficiency is improved about 0.2–0.5 dB compared with previous coding approaches such as H.264/AVC simulcast and JMVM.     

Adaptive multi-modal stereo people tracking without background modelling

Detecting and tracking persons in the sequences of monocular images are the important and difficult problems in computer vision and have been well studied in these two decades. Recently, the methods based on stereo vision have attracted great attentions since 3D information can be exploited. This paper presents an approach for multiple-people detection and tracking using stereo vision. Tracking is carried out using a multiple particle filtering approach that combines depth, colour and gradient information. We modify the degree of confidence assigned to depth information, according to the amount of it found in the disparity map, using a novel confidence measure. The greater the amount of disparity information found, the higher the degree of confidence assigned to depth information in the final particles weights is. In the worst case (total absence of disparity), the proposed algorithm makes use of the information available (colour and gradient) to track, thus performing as a pure colour-based tracking algorithm. People are detected combining an adaboost classifier with stereo information. In order to test the validity of our proposal, it is evaluated in several sequences of colour and disparity images where people interact in complex situations: walk at different distances, shake hands, cross their paths, jump, run, embrace each other and even swap their positions quickly trying to confuse the system. The experimental results show that the proposal is able to deal with occlusions and to effectively determine both the 3D position of the people being tracked and their 2D head locations in the camera image, and everything is realized in real time. Besides, as the proposed method does not require the use of a background model, it can be considered particularly appropriate for applications that must run on mobile devices.     

Adaptive depth truncation filter for MVC based compressed depth image

In multiview video plus depth (MVD) format, virtual views are generated from decoded texture videos with corresponding decoded depth images through depth image based rendering (DIBR). 3DV-ATM is a reference model for the H.264/AVC based multiview video coding (MVC) and aims at achieving high coding efficiency for 3D video in MVD format. Depth images are first downsampled then coded by 3DV-ATM. However, sharp object boundary characteristic of depth images does not well match with the transform coding based nature of H.264/AVC in 3DV-ATM. Depth boundaries are often blurred with ringing artifacts in the decoded depth images that result in noticeable artifacts in synthesized virtual views. This paper presents a low complexity adaptive depth truncation filter to recover the sharp object boundaries of the depth images using adaptive block repositioning and expansion for increasing the depth values refinement accuracy. This new approach is very efficient and can avoid false depth boundary refinement when block boundaries lie around the depth edge regions and ensure sufficient information within the processing block for depth layers classification. Experimental results demonstrate that the sharp depth edges can be recovered using the proposed filter and boundary artifacts in the synthesized views can be removed. The proposed method can provide improvement up to 3.25 dB in the depth map enhancement and bitrate reduction of 3.06% in the synthesized views.     

采用双目立体相机的实时集成成像拍摄系统

提出了一种基于双目立体相机的实时集成成像拍摄系统。不同于采用传统的摄像机阵列,该系统采用双目相机对三维场景进行拍摄,有效地简化了集成成像拍摄系统的结构。该系统首先利用双目相机获取三维场景的左右视差图,然后上传到图形处理器生成三维场景的高分辨率深度图,之后利用深度图和彩色纹理图在图形处理器中并行生成新视点视差图像,并利用像素映射算法生成高分辨率微图像阵列,实现实时的集成成像显示。实验中系统获取的深度图像素数目是微软Kinect2获取深度图像素数目的4.25倍,当系统运行在1 920 pixel1 080 pixel、99视点数的环境下,可实现三维场景的实时拍摄与显示,实验结果证明了所提系统的可行性。     

Reconstruction of lost depth data in multiview video-plus-depth communications using geometric transforms

This paper addresses depth data recovery in multiview video-plus-depth communications affected by transmission errors and/or packet loss. The novel aspects of the proposed method rely on the use of geometric transforms and warping vectors, capable of capturing complex motion and view-dependent deformations, which are not efficiently handled by traditional motion and/or disparity compensation methods. By exploiting the geometric nature of depth information, a region matching approach combined with depth contour reconstruction is devised to achieve accurate interpolation of arbitrary shapes within lost regions of depth maps. The simulation results show that, for different packet loss rates, up to 20%, the depth maps recovered by the proposed method produce virtual views with better quality than existing methods based on motion information and spatial interpolation. An average PSNR gain of 1.48 dB is obtained in virtual views synthesised from depth maps using the proposed method.