Dynamic polygon clouds: representation and compression for VR/AR

Antonio Ortega,Eduardo Pavez,Philip A Chou,Ricardo L De Queiroz

doi:10.1017/atsip.2018.15

Abstract

We introduce the polygon cloud, a compressible representation of three-dimensional geometry (including attributes, such as color), intermediate between polygonal meshes and point clouds. Dynamic polygon clouds, like dynamic polygonal meshes and dynamic point clouds, can take advantage of temporal redundancy for compression. In this paper, we propose methods for compressing both static and dynamic polygon clouds, specifically triangle clouds. We compare triangle clouds to both triangle meshes and point clouds in terms of compression, for live captured dynamic colored geometry. We find that triangle clouds can be compressed nearly as well as triangle meshes, while being more robust to noise and other structures typically found in live captures, which violate the assumption of a smooth surface manifold, such as lines, points, and ragged boundaries. We also find that triangle clouds can be used to compress point clouds with significantly better performance than previously demonstrated point cloud compression methods. For intra-frame coding of geometry, our method improves upon octree-based intra-frame coding by a factor of 5–10 in bit rate. Inter-frame coding improves this by another factor of 2–5. Overall, our proposed method improves over the previous state-of-the-art in dynamic point cloud compression by 33% or more.

Highlights

With the advent of virtual and augmented reality comes the birth of a new medium: live captured three-dimensional (3D) content that can be experienced from any point of view
We find that triangle clouds can be used to compress point clouds with significantly better performance than previously demonstrated point cloud compression methods
Since we are motivated by virtual and augmented reality (VR/AR) applications, for which encoding and decoding have to have low latency, we focus on an approach that can be implemented at low computational complexity

Summary

Introduction

With the advent of virtual and augmented reality comes the birth of a new medium: live captured three-dimensional (3D) content that can be experienced from any point of view Such content ranges from static scans of compact 3D objects to dynamic captures of non-rigid objects such as people, to captures of rooms including furniture, public spaces swarming with people, and whole cities in motion. For such content to be captured at one place and delivered to another for consumption by a virtual or augmented reality device (or by more conventional means), the content needs to be represented and compressed for transmission or storage. Two of the more promising approaches to representing both static and time-varying 3D scenes have

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