Static 3D Triangle Mesh Compression Overview

3D triangle meshes are extremely used to model discrete surfaces, and almost always represented with two tables: one for geometry and another for connectivity. While the raw size of a triangle mesh is of around 200 bits per vertex, by coding cleverly (and separately) those two distinct kinds of information it is possible to achieve compression ratios of 15:1 or more. Different techniques must be used depending on whether single-rate vs. progressive bitstreams are sought; and, in the latter case, on whether or not hierarchically nested meshes are desirable during reconstructio

Efficient 3D data compression through parameterization of free-form surface patches

This paper presents a new method for 3D data compression based on parameterization of surface patches. The technique is applied to data that can be defined as single valued functions; this is the case for 3D patches obtained using standard 3D scanners. The method defines a number of mesh cutting planes and the intersection of planes on the mesh defines a set of sampling points. These points contain an explicit structure that allows us to define parametrically both x and y coordinates. The z values are interpolated using high degree polynomials and results show that compressions over 99% are achieved while preserving the quality of the mesh

3D Model compression using Connectivity-Guided Adaptive Wavelet Transform built into 2D SPIHT

Cataloged from PDF version of article.Connectivity-Guided Adaptive Wavelet Transform based mesh compression framework is proposed. The transformation uses the connectivity information of the 3D model to exploit the inter-pixel correlations. Orthographic projection is used for converting the 3D mesh into a 2D image-like representation. The proposed conversion method does not change the connectivity among the vertices of the 3D model. There is a correlation between the pixels of the composed image due to the connectivity of the 3D mesh. The proposed wavelet transform uses an adaptive predictor that exploits the connectivity information of the 3D model. Known image compression tools cannot take advantage of the correlations between the samples. The wavelet transformed data is then encoded using a zero-tree wavelet based method. Since the encoder creates a hierarchical bitstream, the proposed technique is a progressive mesh compression technique. Experimental results show that the proposed method has a better rate distortion performance than MPEG-3DGC/MPEG-4 mesh coder. © 2009 Elsevier Inc. All rights reserved

Source coding for transmission of reconstructed dynamic geometry: a rate-distortion-complexity analysis of different approaches

Live 3D reconstruction of a human as a 3D mesh with commodity electronics is becoming a reality. Immersive applications (i.e. cloud gaming, tele-presence) benefit from effective transmission of such content over a bandwidth limited link. In this paper we outline different approaches for compressing live reconstructed mesh geometry based on distributing mesh reconstruction functions between sender and receiver. We evaluate rate-performance-complexity of different configurations. First, we investigate 3D mesh compression methods (i.e. dynamic/static) from MPEG-4. Second, we evaluate the option of using octree based point cloud compression and receiver side surface reconstruction

Learning quadrangulated patches for 3D shape parameterization and completion

We propose a novel 3D shape parameterization by surface patches, that are oriented by 3D mesh quadrangulation of the shape. By encoding 3D surface detail on local patches, we learn a patch dictionary that identifies principal surface features of the shape. Unlike previous methods, we are able to encode surface patches of variable size as determined by the user. We propose novel methods for dictionary learning and patch reconstruction based on the query of a noisy input patch with holes. We evaluate the patch dictionary towards various applications in 3D shape inpainting, denoising and compression. Our method is able to predict missing vertices and inpaint moderately sized holes. We demonstrate a complete pipeline for reconstructing the 3D mesh from the patch encoding. We validate our shape parameterization and reconstruction methods on both synthetic shapes and real world scans. We show that our patch dictionary performs successful shape completion of complicated surface textures.Comment: To be presented at International Conference on 3D Vision 2017, 201

ITEM: Inter-Texture Error Measurement for 3D Meshes

We introduce a simple and innovative method to compare any two texture maps, regardless of their sizes, aspect ratios, or even masks, as long as they are both meant to be mapped onto the same 3D mesh. Our system is based on a zero-distortion 3D mesh unwrapping technique which compares two new adapted texture atlases with the same mask but different texel colors, and whose every texel covers the same area in 3D. Once these adapted atlases are created, we measure their difference with ITEM-RMSE, a slightly modified version of the standard RMSE defined for images. ITEM-RMSE is more meaningful and reliable than RMSE because it only takes into account the texels inside the mask, since they are the only ones that will actually be used during rendering. Our method is not only very useful to compare the space efficiency of different texture atlas generation algorithms, but also to quantify texture loss in compression schemes for multi-resolution textured 3D meshes

Partial differential equations for 3D Data compression and Reconstruction

This paper describes a Partial Differential Equation (PDE) based method for 3D reconstruction of surface patches. The PDE method is exploited using data obtained from standard 3D scanners. First the original surface data are sparsely re-meshed by a number of cutting planes whose intersection points on the mesh are represented by Fourier coefficients in each plane. Information on the number of vertices and scale of the surface are defined and, together, these efficiently define the compressed data. The PDE method is then applied at the reconstruction stage by defining PDE surface patches between the sparse cutting planes recovering thus, the vertex density of the original mesh. Results show that compression rates over 96% are achieved while preserving the quality of the 3D mesh. The paper discusses the suitability of the method to a number of applications and general issues in 3D compression and reconstruction

Image-Based Compression Method of Three-Dimensional Range Data with Texture

Recently, high speed and high accuracy three-dimensional (3D) scanning techniques and commercially available 3D scanning devices have made real-time 3D shape measurement and reconstruction possible. The conventional mesh representation of 3D geometry, however, results in large file sizes, causing difficulties for its storage and transmission. Methods for compressing scanned 3D data therefore become desired. This paper proposes a novel compression method which stores 3D range data within the color channels of a regular 2D output image. Our method encodes the 3D range data’s respective normalized phase map, generated by a virtual stereovision system, into two of the output image’s color channels using space filling curves. The remaining color channel is used to store a texture image. Once the data is encoded within the 2D output image, lossless or lossy 2D image and video compression techniques can be taken advantage of to further compress the data. The compressed image/video can later be decoded to reconstruct original 3D range data using the calibration parameters of the virtual stereovision system. Experiments verify that the proposed method accurately recovers both geometry and texture information, while achieving high compression ratios. For example, comparing with the OBJ mesh format, lossless PNG storage of our method’s encoded image achieved a 98:1 compression ratio with almost no loss of quality; lossy JPEG with 85% quality achieved a 618:1 compression ratio with a slight loss of quality; and H.264 video compression achieved a 1421:1 compression ratio for a sequence of consecutively recorded frames. As the proposed encoding and decoding process can be applied to most of the current platforms, this novel compression method can help make 3D data storage and transmission immediately available for many different devices