Efficient Coding of Nontriangular Mesh Connectivity

We describe an efficient algorithm for coding the connectivity information of general polygon meshes. In contrast to most existing algorithms which are suitable only for triangular meshes, and pay a penalty for treatment of nontriangular faces, this algorithm codes the connectivity information in a direct manner. Our treatment of the special case of triangular meshes is shown to be equivalent to the Edgebreaker algorithm. Using our methods, any triangle mesh may be coded in no more than 2 bits/triangle (approximately 4 bits/vertex), a quadrilateral mesh in no more than 3.5 bits/quad (approximately 3.5 bits/vertex), and the most common case of a quad mesh with few triangles in no more than 4 bits/polygon.     

Delphi: geometry-based connectivity prediction in triangle mesh compression

Delphi is a new geometry-guided predictive scheme for compressing the connectivity of triangle meshes. Both compression and decompression algorithms traverse the mesh using the EdgeBreaker state machine. However, instead of encoding the EdgeBreaker clers symbols that capture connectivity explicitly, they estimate the location of the unknown vertex, v , of the next triangle. If the predicted location lies sufficiently close to the nearest vertex, w , on the boundary of the previously traversed portion of the mesh, then Delphi estimates that v coincides with w . When the guess is correct, a single confirmation bit is encoded. Otherwise, additional bits are used to encode the rectification of that prediction. When v coincides with a previously visited vertex that is not adjacent to the parent triangle (EdgeBreaker S case), the offset, which identifies the vertex v , must be encoded, mimicking the cut-border machine compression proposed by Gumhold and Strasser. On models where 97% of Delphi predictions are correct, the connectivity is compressed down to 0.19 bits per triangle. Compression rates decrease with the frequency of wrong predictors, but remains below 1.50 bits per triangle for all models tested.     

Advancing fan-front: 3D triangle mesh compression using fan based traversal

Connectivity compression techniques for very large 3D triangle meshes are based on clever traversals of the graph representing the mesh, so as to avoid the repeated references to vertices. In this paper we present a new algorithm for compressing large 3D triangle meshes through the successive conquest of triangle fans. The connectivity of vertices in a fan is implied. As each fan is traversed, the current mesh boundary is advanced by the fan-front. The process is recursively continued till the entire mesh is traversed. The mesh is then compactly encoded as a sequence of fan configuration codes. The fan configuration code comprehensively encodes the connectivity of the fan with the rest of the mesh. There is no need for any further special operators like split codes and additional vertex offsets. The number of fans is typically one-fourth of the total number of triangles. Only a few of the fan configurations occur with high frequency, enabling excellent connectivity information compression using range encoding. A simple implementation shows significant improvements, on the average, in bit-rate per vertex, compared to earlier reported techniques.     

基于小波变换的非渐进网格压缩

为了取得较好的三角形网格压缩性能，提出了一种基于小波变换的三角形网格非渐进压缩方法。该压缩方法先利用重新网格化来去除大部分连接信息，然后利用小波变换的强去相关能力来压缩几何信息。在进行重新网格化和小波变换后，再按一个确定的次序将所有的小波系数扫描为一个序列，然后对其做量化和算术编码。另外，对重新网格化得到的自适应半正规采样模式，还设计了一种自适应细分信息编码算法，以便使解码端知道每一个小波系数应该放置在哪一个顶点上。实验表明，用该压缩方法对由三维扫描仪获取的复杂网格进行压缩，取得了比Edgebreaker方法明显要好的率失真性能；10比特量化时，压缩倍数在200倍左右，为Edgebreaker方法的2倍多。     

Random Accessible Hierarchical Mesh Compression for Interactive Visualization

This paper presents a novel algorithm for hierarchical random accessible mesh decompression. Our approach progressively decompresses the requested parts of a mesh without decoding less interesting parts. Previous approaches divided a mesh into independently compressed charts and a base coarse mesh. We propose a novel hierarchical representation of the mesh. We build this representation by using a boundary-based approach to recursively split the mesh in two parts, under the constraint that any of the two resulting submeshes should be reconstructible independently.
In addition to this decomposition technique, we introduce the concepts of opposite vertex and context dependant numbering . This enables us to achieve seemingly better compression ratios than previous work on quad and higher degree polygonal meshes. Our coder uses about 3 bits per polygon for connectivity and 14 bits per vertex for geometry using 12 bits quantification.     

Optimized Edgebreaker encoding for large and regular triangle meshes

We present a technique aiming to improve the compression of the Edgebreaker CLERS string for large and regular meshes, where regularity is understood as the compactness of the distribution of vertex degrees. Our algorithm uses a specially designed context-based coding to compress the CLERS sequence. It is exceptionally simple to implement and can easily be incorporated into any existing Edgebreaker implementation which uses the Spirale Reversi algorithm for decompression. Even for irregular meshes, it does not carry considerable overhead when compared to the original Edgebreaker encoding. Experimental results show that our procedure is very fast (600000 triangles per second on a PIII 650 MHz for decompression) and leads to compression rates which are, in most cases, superior to those previously reported for large meshes of high regularity.     

三维图形数据的压缩与网上浏览

尽管互联网上存在着大量的压缩图像,但互联网上的三维图形数据却很少,其中一个重要原因就是三维图形数据的数据量比较大,所以要进行高效的压缩,以节约存储空间和网络带宽。文章结合Edgebreaker连接关系编码算法、平行四边形顶点坐标预测以及算术编码,来实现三角形网格的压缩,得到了50倍左右的压缩比;然后设计了一种存储压缩三维图形数据的eb文件格式,实现了一个支持网上浏览压缩三维图形数据的IE浏览器插件,可用于三维网页、数字博物馆等应用中。     

Compressed progressive meshes

Most systems that support visual interaction with 3D models use shape representations based on triangle meshes. The size of these representations imposes limits on applications for which complex 3D models must be accessed remotely. Techniques for simplifying and compressing 3D models reduce the transmission time. Multiresolution formats provide quick access to a crude model and then refine it progressively. Unfortunately, compared to the best nonprogressive compression methods, previously proposed progressive refinement techniques impose a significant overhead when the full resolution model must be downloaded. The CPM (compressed progressive meshes) approach proposed here eliminates this overhead. It uses a new technique, which refines the topology of the mesh in batches, which each increase the number of vertices by up to 50 percent. Less than an amortized total of 4 bits per triangle encode where and how the topological refinements should be applied. We estimate the position of new vertices from the positions of their topological neighbors in the less refined mesh using a new estimator that leads to representations of vertex coordinates that are 50 percent more compact than previously reported progressive geometry compression techniques     

一种新的三角形网格压缩算法

现代图形应用系统需要绘制大量的几何体，这给绘制硬件带来内存、带宽等问题。解决该问题的方法之一就是在预处理阶段对静态三维几何物体进行压缩处理。本文提出了一种新的三角形网格压缩／解压缩算法，该算法将三角形网格分解成一组三角形条和序列顶点链，然后对顶点连通性进行熵缟码。该算法与已有的GTM压缩算法相比，压缩率提
高了32％，并且支持并行解压缩。本文还提出了一种平行四边形预测方法来压缩顶点坐标。     

三角形条带网格模型几何压缩方法研究

三角形条带为三角形网格提供了一种紧凑的表示方法，使快速的绘制和传输三角形网格成为可能，因此对由三角形条带构成的网格压缩进行研究具有重要的意义．本文使用Triangle Fixer方法对三角形条带构成的三维模型拓扑信息进行了压缩，并采用3阶自适应算术编码进一步提高压缩率；同时结合量化、平行四边形顶点坐标预测以及算术编码来实现三角形网格几何信息的压缩，在几何模型质量基本没有损失的情况下，获得了很好的压缩性能．     

A Parallel Approach to Compression and Decompression of Triangle Meshes using the GPU

Most state‐of‐the‐art compression algorithms use complex connectivity traversal and prediction schemes, which are not efficient enough for online compression of large meshes. In this paper we propose a scalable massively parallel approach for compression and decompression of large triangle meshes using the GPU. Our method traverses the input mesh in a parallel breadth‐first manner and encodes the connectivity data similarly to the well known cut‐border machine. Geometry data is compressed using a local prediction strategy. In contrast to the original cut‐border machine, we can additionally handle triangle meshes with inconsistently oriented faces. Our approach is more than one order of magnitude faster than currently used methods and achieves competitive compression rates.     

Zipper: A compact connectivity data structure for triangle meshes

We propose Zipper, a compact representation of incidence and adjacency for manifold triangle meshes with fixed connectivity. Zipper uses on average only 6 bits per triangle, can be constructed in linear space and time, and supports all standard random-access and mesh traversal operators in constant time. Similarly to the previously proposed LR (Laced Ring) approach, the Zipper construction reorders vertices and triangles along a nearly Hamiltonian cycle called the ring. The 4.4× storage reduction of Zipper over LR results from three contributions. (1) For most triangles, Zipper stores a 2-bit delta (plus three additional bits) rather than a full 32-bit reference. (2) Zipper modifies the ring to reduce the number of exceptional triangles. (3) Zipper encodes the remaining exceptional triangles using 2.5× less storage. In spite of these large savings in storage, we show that Zipper offers comparable performance to LR and other data structures in mesh processing applications. Zipper may also serve as a compact indexed format for rendering meshes, and hence is valuable even in applications that do not require adjacency information.     

基于模版的三角网格拓扑压缩

提出一种基于面的高效三角网格拓扑压缩算法.该算法是单分辨率无损压缩算法,是对Edgebreaker算法的改进:在网格遍历部分,通过自适应网格遍历方法使非常影响压缩比的分割图形操作尽可能少;在熵编码部分,为网格遍历后得到的每个操作符各设计一个模版,根据模版确定该操作符的二进制表示,然后采用自适应算术编码方法压缩该二进制表示得到最后的压缩结果.与网格拓扑压缩领域中基于面的最好的算法得到的压缩比相比较,该算法得到的压缩比有很大提高.     

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.     

子分元素法:一种体网格压缩算法

提出了一个包含六面体,四面体,金字塔以及三棱柱单元的混合体网格的压缩与解压算法。首先对非四面体单元按照最小节点标号策略进行子分,然后利用修改的增长缝合算法压缩子分后的四面体网格,解压阶段再通过面删除操作来恢复原始网格。压缩后每个四面体约需10bits的存储,初步试验表明,对于通常的六面体网格,能将数据模型压缩至原先的1／4。     

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.      

Data‐Parallel Decompression of Triangle Mesh Topology

We propose a lossless, single‐rate triangle mesh topology codec tailored for fast data‐parallel GPU decompression. Our compression scheme coherently orders generalized triangle strips in memory. To unpack generalized triangle strips efficiently, we propose a novel parallel and scalable algorithm. We order vertices coherently to further improve our compression scheme. We use a variable bit‐length code for additional compression benefits, for which we propose a scalable data‐parallel decompression algorithm. For a set of standard benchmark models, we obtain (min: 3.7, med: 4.6, max: 7.6) bits per triangle. Our CUDA decompression requires only about 15% of the time it takes to render the model even with a simple shader.     

Multilevel representation and transmission of real objects with progressive octree particles

We present a multilevel representation scheme adapted to storage, progressive transmission, and rendering of dense data sampled on the surface of real objects. Geometry and object attributes, such as color and normal, are encoded in terms of surface particles associated to a hierarchical space partitioning based on an octree. Appropriate ordering of surface particles results in a compact multilevel representation without increasing the size of the uniresolution model corresponding to the highest level of detail. This compact representation can progressively be decoded by the viewer and transformed by a fast direct triangulation technique into a sequence of triangle meshes with increasing levels of detail. The representation requires approximately 5 bits per particle (2.5 bits per triangle) to encode the basic geometrical structure. The vertex positions can then be refined by means of additional precision bits, resulting in 5 to 9 bits per triangle for representing a 12-bit quantized geometry. The proposed representation scheme is demonstrated with the surface data of various real objects.     

Distance-Ranked Connectivity Compression of Triangle Meshes

We present a new, single-rate method for compressing the connectivity information of a connected 2-manifold triangle mesh with or without boundary. Traditional compression schemes interleave geometry and connectivity coding, and are thus typically unable to utilize information from vertices (mesh regions) they have not yet processed. With the advent of competitive point cloud compression schemes, it has become feasible to develop separate connectivity encoding schemes that can exploit complete, global vertex position information to improve performance. Our scheme demonstrates the utility of this separation of vertex and connectivity coding. By traversing the mesh edges in a consistent fashion, and using global vertex information, we can predict the position of the vertex that completes the unprocessed triangle attached to a given edge. We then rank the vertices in the neighborhood of this predicted position by their Euclidean distance. The distance rank of the correct closing vertex is stored. Typically, these rank values are small, and the set of rank values thus possesses low entropy and compresses very well. The sequence of rank values is all that is required to represent the mesh connectivity—no special split or merge codes are necessary. Results indicate improvements over traditional valence-based schemes for more regular triangulations. Highly irregular triangulations or those containing a large number of slivers are not well modelled by our current set of predictors and may yield poorer connectivity compression rates than those provided by the best valence-based schemes.     

Compressing Triangulated Irregular Networks

We address the problem of designing compact data structures for encoding a Triangulated Irregular Network (TIN). In particular, we study the problem of compressing connectivity, i.e., the information describing the topological structure of the TIN, and we propose two new compression methods which have different purposes. The goal of the first method is to minimize the number of bits needed to encode connectivity information: it encodes each vertex once, and at most two bits of connectivity information for each edge of a TIN; algorithms for coding and decoding the corresponding bitstream are simple and efficient. A practical evaluation shows compression rates of about 4.2 bits per vertex, which are comparable with those achieved by more complex methods. The second method compresses a TIN at progressive levels of detail and it is based on a strategy which iteratively removes a vertex from a TIN according to an error-based criterion. Encoding and decoding algorithms are presented and compared with other approaches to progressive compression. Our method can encode more general types of triangulations, such as those constrained by topographic features, at the cost of a slightly longer bitstream.