The rapid development of Virtual Environments (VEs) gives rise to its prominent performance in a myriad of multimedia applications. Accompanied by this is the increasingly massive data used for ascending user's visual experience. Recently, 3D streaming makes it viable to put VEs into real-time use through progressive transmission. Nonetheless, downloading VEs over inevitable lossy networks still remains a major bottleneck that urgently needs to be solved. In this paper, we propose a three-stage progressive transmission scheme for VEs over lossy networks, which aims to minimize distortion even when encountering poor network condition. The first stage is the Pre-coding Stage that offers the most feasible transmission scheme for subsequent transmission, in this stage we combine the advanced interest management algorithm and our proposed scene distortion estimation algorithm to bring up a scene update strategy which takes the user's visual features, quality of the scene and bandwidth estimation into account, so as to determine the download priority comprehensively. In the following Transmitting Stage, we apply Transmission Control Protocol (TCP) to make sure that we convey the essential information. More importantly, we adopt expanding window fountain (EWF) codes to provide an unequal error protection (UEP) for data with different importance. Eventually in the third After-process Stage, we employ a geometry prediction algorithm for the scenario with packet loss. The final results of our experiments show that the three-stage scheme can offer preeminent visual experience especially when it comes to a relatively inferior network condition.

/pdf/a-three-stage-progressive-transmission-scheme-for-virtual-hcjoapetm7.pdf

A Three-Stage Progressive Transmission Scheme for Virtual Environments Over Lossy Networks

Virtual environments (VEs) have been widely used in multimedia applications, with trends toward larger data size. 3D streaming has recently been proposed to enable users to view the VEs in real time. However, how to efficiently download the VEs over a bandwidth-limited network becomes a bottleneck. With the aim of minimizing the scene distortion and achieving a more efficient use of bandwidth, it’s necessary to download the visible 3D contents at an appropriate resolution. In this paper, we propose a distortion-aware VEs transmission scheme. The main contributions of the proposed scheme include: (1) Improving the traditional interest management algorithm, so that our method can fit the user’s visual and behavioral characteristics better. (2) Proposing a scene distortion estimation algorithm, by which we can effectively calculate and evaluate the scene distortion. (3) Based on (1) and (2), we propose a scene update strategy, which combines the user’s visual characteristics, scene distortion and bandwidth estimation. The experimental results show that the proposed scheme can lower distortion especially when network condition is poor.

Distortion-aware Virtual Environments Transmission Scheme over a Bandwidth-limited Network

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Jingfeng Guo

Author Tools

Chat about Author

Papers

Distortion-aware Virtual Environments Transmission Scheme over a Bandwidth-limited Network