三维网格单一位率压缩统一框架的设计与实现

三维网格单一位率压缩技术将网格的几何信息和拓扑连接信息分开独立压缩.进行连接信息压缩时,通常对某种结构表示的网格连接信息进行某种形式的遍历,对遍历过程进行信息编码压缩;压缩几何信息时,一般需要经过量化、预测和熵编码3个处理过程.通过对该类算法进行研究总结,提出并设计了一个针对三角网格的单一位率压缩统一模式框架,并基于OpenGL和Visual C 6.0,以Edgebreaker算法为例进行了实验.     

Reconstruction Algorithms as a Suitable Basis for Mesh Connectivity Compression

During a highly productive period running from 1995 to about 2002, the research in lossless compression of surface meshes mainly consisted in a hard battle for the best bitrates. However, for a few years, compression rates seem stabilized around 1.5 bit per vertex for the connectivity coding of usual triangular meshes, and more and more work is dedicated to remeshing, lossy compression, or gigantic mesh compression, where memory access and CPU optimizations are the new priority. However, the size of 3D models keeps growing, and many application fields keep requiring lossless compression. In this paper, we present a new contribution for single-rate lossless connectivity compression, which first brings improvement over current state of the art bitrates, and second, does not constraint the coding of the vertex positions, offering therefore a good complementarity with the best performing geometric compression methods. The initial observation having motivated this work is that very often, most of the connectivity part of a mesh can be automatically deduced from its geometric part using reconstruction algorithms. This has already been used within the limited framework of projectable objects (essentially, terrain models and GIS), but finds here its first generalization to arbitrary triangular meshes, without any limitation regarding the topological genus, the number of connected components, the manifoldness or the regularity. This can be obtained by constraining and guiding a Delaunay-based reconstruction algorithm so that it outputs the initial mesh to be coded. The resulting rates seem extremely competitive when the meshes are fully included in Delaunay, and are still good compared to the state-of-the-art in the case of scanned models.      

基于单幅图像的真实感人体动画合成

由于单幅图像缺失三维信息以及完整的纹理信息,基于单幅图像的真实感三维人体动画合成极具挑战性。针对单幅图像三维信息缺失问题,提出了一种基于SMPL参数模型的三维人体几何重建方法。该方法以单幅图像为输入,先根据输入图像人体轮廓信息变形标准的SMPL参数模型分别生成与目标轮廓一致的正反面的三维几何模型,然后利用基于B样条插值的网格拼接融合算法拼接正反面三维几何,最后为了恢复正确的手部几何,利用基于B样条插值的网格拼接融合算法,将重建后的模型上错误的手部几何用标准SMPL参数模型上正确的手部几何替换。同时,针对单幅图像中纹理缺失的问题,提出了一个称为FBN（front to back network）的对抗生成网络,用于恢复被遮挡的人体背面纹理。实验结果表明,该方法生成的具有完整纹理的人体几何能够由3D运动数据驱动运动,生成具有高度真实感的三维人体动画。     

新颖的网格模型压缩算法——网格切片

针对三维(3D)网格模型的存储与网络传输问题,提出一种新颖的三维模型压缩算法。该算法基于对网格模型的切片处理,主要由以下三个步骤组成:切片顶点的计算、切片边界的均匀采样以及对切片所得图像的编码。对于一个给定的三维模型,首先,计算模型的包围盒;然后,沿包围盒长度最长的方向进行切片;同时计算切片与网格模型表面每条边的交点,构成一个多边形,这个多边形即为切片的边界;其次,对切片边界进行均匀的重采样,使每层切片具有相同的顶点数;最后,把每层的顶点坐标转化为极坐标形式,这样,所有层顶点的ρ-坐标以及θ-坐标能分别构成一张图像,原始的三维模型即能由这两张图像表示。这种表示方法具有以下两个明显的优势:第一,降低了数据的维度,有效减少了数据量;第二,具有极大的数据相关性,进一步减少了数据的熵。基于这两个优势,该算法对图像数据进行差值编码以及算术编码,最后得到压缩后的文件。与增量参数细化(IPR)方法相比,在解码模型同等质量的前提下,所提算法的编码效率提高了23%。实验结果表明,所提算法在模型存储和传输应用中能取得很好的压缩效率,有效减少了数据量。     

Geometric signal compression

Compression of mesh attributes becomes a challenging problem due to the great need for efficient storage and fast transmission. This paper presents a novel geometric signal compression framework for all mesh attributes, including position coordinates, normal, color, texture, etc. Within this framework, mesh attributes are regarded as geometric signals defined on mesh surfaces. A planar parameterization algorithm is first proposed to map 3D meshes to 2D parametric meshes. Geometric signals are then transformed into 2D signals, which are sampled into 2D regular signals using an adaptive sampling method. The JPEG2000 standard for still image compression is employed to effectively encode these regular signals into compact bit-streams with high rate/distortion ratios. Experimental results demonstrate the great application potentials of this framework.     

基于小波半规则网格压缩均方误差的近似方法

为了实现数据量大的图像在网络上的快速传输,就必须对其进行高压缩。现在一般采用比较先进的小波压缩方法,但用压缩后的数据重构得到的图像与原图像相比有明显的差别。为了降低这种失真,开始部分提出了一种有效的基于位分配模型的性能优化方法;为了实现这种快速和低复杂度的分配方法,提出了和半规则网格几何编码相关的重建均方误差的近似方法。并用实验结果说明,在基于模型分配的过程中将上述近似方法得到的结果作为失真可以改善小波编码器的性能,提高编码增益,从而达到在不降低图像压缩率下提高图像质量的目的。     

R-D optimized progressive compression of 3D meshes using prioritized gate selection and curvature prediction

A rate-distortion (R-D) optimized progressive coding algorithm for three-dimensional (3D) meshes is proposed in this work. We propose the prioritized gate selection and the curvature prediction to improve the connectivity and geometry compression performance, respectively. Furthermore, based on the bit plane coding, we develop a progressive transmission method, which improves the qualities of intermediate meshes as well as that of the fully reconstructed mesh, and extend it to the view-dependent transmission method. Experiments on various 3D mesh models show that the proposed algorithm provides significantly better compression performance than the conventional algorithms, while supporting progressive reconstruction efficiently.     

Image‐Based Surface Compression

We present a generic framework for compression of densely sampled three‐dimensional (3D) surfaces in order to satisfy the increasing demand for storing large amounts of 3D content. We decompose a given surface into patches that are parameterized as elevation maps over planar domains and resampled on regular grids. The resulting shaped images are encoded using a state‐of‐the‐art wavelet image coder. We show that our method is not only applicable to mesh‐ and point‐based geometry, but also outperforms current surface encoders for both primitives.     

Geometric Snakes for Triangular Meshes

Feature detection is important in various mesh processing techniques, such as mesh editing, mesh morphing, mesh compression, and mesh signal processing. In spite of much research in computer vision, automatic feature detection even for images still remains a difficult problem. To avoid this difficulty, semi‐automatic or interactive techniques for image feature detection have been investigated. In this paper, we propose a geometric snake as an interactive tool for feature detection on a 3D triangular mesh. A geometric snake is an extension of an image snake, which is an active contour model that slithers from its initial position specified by the user to a nearby feature while minimizing an energy functional. To constrain the movement of a geometric snake onto the surface of a mesh, we use the parameterization of the surrounding region of a geometric snake. Although the definition of a feature may vary among applications, we use the normal changes of faces to detect features on a mesh. Experimental results demonstrate that geometric snakes can successfully capture nearby features from user‐specified initial positions.     

Silhouette‐Aware Warping for Image‐Based Rendering

Image‐based rendering (IBR) techniques allow capture and display of 3D environments using photographs. Modern IBR pipelines reconstruct proxy geometry using multi‐view stereo, reproject the photographs onto the proxy and blend them to create novel views. The success of these methods depends on accurate 3D proxies, which are difficult to obtain for complex objects such as trees and cars. Large number of input images do not improve reconstruction proportionally; surface extraction is challenging even from dense range scans for scenes containing such objects. Our approach does not depend on dense accurate geometric reconstruction; instead we compensate for sparse 3D information by variational image warping. In particular, we formulate silhouette‐aware warps that preserve salient depth discontinuities. This improves the rendering of difficult foreground objects, even when deviating from view interpolation. We use a semi‐automatic step to identify depth discontinuities and extract a sparse set of depth constraints used to guide the warp. Our framework is lightweight and results in good quality IBR for previously challenging environments.     

改进的分形矢量量化编码

为了提高图象的分形矢量量化编码效果，在利用四叉树对图象进行自适应分割的基础上，基于正交基三维分量投影准则，提出了图象块非平面近似方法，进而形成一种新的静态图象分形矢量量化编码方法。该方法首先通过对投影参数进行DPCM编码来构造粗糙图象，然后由此来构成差值图象编码的码书。由于该方法把分形和矢量量化编码结合起来，因此解码时只需查找码书，并仅进行对比度变换。计算机编、解码实验结果表明，该编码方法具有码书不需外部训练，解码也不需迭代等优点，且与其他同类编码器相比，该方法在压缩比和恢复图象质量（PSRN）方面均有明显改善。     

一种新的RGB空间的彩色图像编码方法

为了能够较好地去除彩色图像色彩分量的相关性, 并能获得较好的恢复图像, 基于图像色彩信息, 提出了一种基于RGB空间的彩色图像压缩编码算法, 高效地去除了彩色图像各分量间的相关性。算法对其中一个分量进行完整DCT变换,对其他两个分量只求少数几个非零系数。采用查表法来进行DCT变换,使查表法的优越性得到更好的体现。通过对新色彩空间编码性能进行的实验分析结果表明, 该方法较好地去除了彩色图像色彩分量的相关性, 且算法实现简单, 具有较好的信噪比, 不仅恢复图像视觉效果良好, 并且易于与其他的压缩、编码方法结合     

基于小波包分解的 SAR图像压缩 *

针对 SAR图像含有丰富的中、高频信息 ,而基于小波变换的图像压缩方法会丢失高频细节信息 ,提出了基于小波包分解的 SAR图像编码算法。小波包变换对 SAR图像进行完全分解 ,再用与后续编码器相关联的代价函数进行最佳基搜索 ,然后根据各子带小波包系数的重要性进行加权 ,采用多级树集合分裂算法 ( SPIHT)编码。实验结果表明 ,该算法更好地保留了 SAR图像的细节信息 ,获得了同压缩比下优于传统 SPIHT算法的编码性能 ,更有利于后续图像处理。     

Implementation of 3D mesh streaming and compression techniques in NVEs

In this paper, we present a framework that integrates three‐dimensional (3D) mesh streaming and compression techniques and algorithms into our EVE‐II networked virtual environments (NVEs) platform, in order to offer support for large‐scale environments as well as highly complex world geometry. This framework allows the partial and progressive transmission of 3D worlds as well as of separate meshes, achieving reduced waiting times for the end‐user and improved network utilization. We also present a 3D mesh compression method focused on network communication, which is designed to support progressive mesh transmission, offering a fast and effective means of reducing the storage and transmission needs for geometrical data. This method is integrated in the above framework and utilizes prediction to achieve efficient lossy compression of 3D geometry. Copyright © 2006 John Wiley & Sons, Ltd.     

Learning 3D Deformation of Animals from 2D Images

Understanding how an animal can deform and articulate is essential for a realistic modification of its 3D model. In this paper, we show that such information can be learned from user‐clicked 2D images and a template 3D model of the target animal. We present a volumetric deformation framework that produces a set of new 3D models by deforming a template 3D model according to a set of user‐clicked images. Our framework is based on a novel locally‐bounded deformation energy, where every local region has its own stiffness value that bounds how much distortion is allowed at that location. We jointly learn the local stiffness bounds as we deform the template 3D mesh to match each user‐clicked image. We show that this seemingly complex task can be solved as a sequence of convex optimization problems. We demonstrate the effectiveness of our approach on cats and horses, which are highly deformable and articulated animals. Our framework produces new 3D models of animals that are significantly more plausible than methods without learned stiffness.     

三维面模型的几何压缩技术综述

随着应用需求的增长,三维模型的规模和复杂度急剧增长,给模型的存储和在有限带宽的网络上传输带来了很大的困难.因此,研究空间需求小、适合于计算机网络传输的三维模型的表示方法具有十分重要的意义.三维模型的压缩主要包括拓扑压缩和几何压缩.由于压缩数据中的大部分是几何压缩数据,因此已发展了许多几何压缩方法,以提高模型的压缩效率.为使相关的学者和工程技术人员较好地了解几何压缩技术,本文对这方面的工作进行了较全面的介绍.本文首先介绍了几何压缩的基本流程及几种几何压缩方法的分类原则,然后将几何压缩技术分为基础压缩方法和经过模型变换的压缩方法两大类并分别进行详细的介绍,讨论了各个方法的特点,最后结合我们自身的工作认识对几何压缩技术进行小结和展望.     

基于薄板样条变换的几何图像序列压缩方法

为了提高对几何图像序列的压缩效率,本文提出一种基于薄板样条函数（ThinPlateSpine,TPS）的有损压缩算法。在该压缩算法中,利用TPS变换可用于三维表面形变的特点,将TPS变换作为几何图像序列中相邻帧之间从前一帧到后一帧的预测器,通过存储TPS变换矩阵系数的方式编码预测帧,将该方法应用于一个三维人脸网格的几何图像序列,获得了较好的压缩效果。     

3D geometry-dependent texture map compression with a hybrid ROI coding

Difering from common 2D images,a texture map,since it is used to project onto a 3D model in 3D space,not only contains 2D texture information,but also implicitly associates certain 3D geometric information.Related to this,an efective 3D geometry-dependent texture map compression method with hybrid region of interest(ROI)coding is proposed in this paper.We regard the visually important area of the texture map as the ROI.To acquire the visually important areas of the texture map,we take into account information from both the 3D geometry and 2D texture maps,depicting the saliency of the textured model,distortion of the texture mapping,and boundary of the texture atlas.These visually important areas are expressed as a visual importance map.According to the particularity of the texture map,a hybrid ROI coding method that utilizes Max-Shift and an improved post compression rate distortion(PCRD)technique is presented,guided by this visual importance map.To find the exact wavelet coefcients pertaining to these ROIs before carrying out the hybrid ROI coding,this paper proposes a stochastic coefcient priority mask map computational method.Experimental results show that the visually important areas of the texture image have a better visual efect and that a good rendering result can be obtained from the texture mapping.