Abstract

Point cloud video provides 6 degrees of freedom (6DoF) viewing experiences to allow users to freely select the viewing angles of 3D scenes and is expected to be the next-generation video. This paper studies the point cloud video streaming and proposes a fuzzy logic-based point cloud video streaming scheme to solve the inherent technical issues. In particular, a point cloud video is first partitioned into smaller tiles, along with a low-quality base layer covering the entire video. Each tile is encoded into different quality levels, and both the compressed and uncompressed (i.e., decoded) versions of each tile are prepared for selection. Then, based on the user's viewing angle and predicted future network bandwidth condition, fuzzy logic empowered quality level selection, with properly defined novel fuzzification, fuzzy rules, and defuzzification, is conducted to maximize the received point cloud video quality under the communication resource, computational resource and quality requirements constraints. Extensive simulations based on real point cloud video sequences and network traces are conducted, and the results reveal the superiority of the proposed scheme over the baseline scheme. To the best of our knowledge, this is the first work studying point cloud video streaming using fuzzy logic.

Highlights

  • With the development of video capturing and transmission technologies, immersive video such as virtual reality (VR) video [1], which allows free selection of the viewing direction, has become increasingly popular [2]

  • Extensive simulations based on real point cloud video sequences and network traces are conducted, and the results reveal the superiority of the proposed scheme over the baseline scheme

  • This paper focuses on point cloud video streaming, which has recently become a research hotspot [10]–[15] and aims to solve the inherent technical issues to provide users with higher video quality

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Summary

INTRODUCTION

With the development of video capturing and transmission technologies, immersive video such as virtual reality (VR) video [1], which allows free selection of the viewing direction, has become increasingly popular [2]. Based on the user’s viewing angle, future network bandwidth, available computational resource and quality requirements, a fuzzy logic empowered quality level selection method is proposed with properly defined novel fuzzification, fuzzy rules, and defuzzification This fuzzy logic empowered scheme considers the unique features of the point cloud video streaming system, which includes the status of the available computations for decoding and channel bandwidth changes, and helps maximize the received point cloud video quality under the communication resource, computational resource and user quality requirements constraints. With properly defined novel fuzzification, fuzzy rules, and defuzzification, a fuzzy logic empowered quality level selection scheme is proposed to help maximize the received point cloud video quality, which considers the future viewing angle, network condition, and available r computational resource.

POINT CLOUD VIDEO ENCODING AND PROCESSING
CONSTRAINTS AND OBJECTIVE We first define two indicator notations
FUZZY LOGIC EMPOWERED QUALITY LEVEL SELECTION
SIMULATION RESULTS
CONCLUSION
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