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Novel 3D Compression Methods for Geometry, Connectivity and Texture

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3D Research

Abstract

A large number of applications in medical visualization, games, engineering design, entertainment, heritage, e-commerce and so on require the transmission of 3D models over the Internet or over local networks. 3D data compression is an important requirement for fast data storage, access and transmission within bandwidth limitations. The Wavefront OBJ (object) file format is commonly used to share models due to its clear simple design. Normally each OBJ file contains a large amount of data (e.g. vertices and triangulated faces, normals, texture coordinates and other parameters) describing the mesh surface. In this paper we introduce a new method to compress geometry, connectivity and texture coordinates by a novel Geometry Minimization Algorithm (GM-Algorithm) in connection with arithmetic coding. First, each vertex (x, y, z) coordinates are encoded to a single value by the GM-Algorithm. Second, triangle faces are encoded by computing the differences between two adjacent vertex locations, which are compressed by arithmetic coding together with texture coordinates. We demonstrate the method on large data sets achieving compression ratios between 87 and 99 % without reduction in the number of reconstructed vertices and triangle faces. The decompression step is based on a Parallel Fast Matching Search Algorithm (Parallel-FMS) to recover the structure of the 3D mesh. A comparative analysis of compression ratios is provided with a number of commonly used 3D file formats such as VRML, OpenCTM and STL highlighting the performance and effectiveness of the proposed method.

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Authors and Affiliations

  1. GMPR-Geometric Modelling and Pattern Recognition Research Group, Sheffield Hallam University, Sheffield, UK

    M. M. Siddeq & M. A. Rodrigues

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  1. M. M. Siddeq
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  2. M. A. Rodrigues
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Correspondence to M. M. Siddeq.

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Siddeq, M.M., Rodrigues, M.A. Novel 3D Compression Methods for Geometry, Connectivity and Texture. 3D Res 7, 13 (2016). https://doi.org/10.1007/s13319-016-0091-x

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  • DOI: https://doi.org/10.1007/s13319-016-0091-x

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