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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 5

Fast coding algorithm based on predictive partition convolutional neural network for 360-degree video

Xiang Hai
Chen Fen
Qin Yiqing
Li Xu
Peng Zongju
School of Electrical & Electronic Engineering, Chongqing University of Technology, Chongqing 400054, China
DOI: 10.19734/j.issn.1001-3695.2024.07.0350

Abstract

In order to solve the problem of excessive complexity of 360-degree video based on equirectangular projection (ERP) of versatile video coding (VVC) , this paper proposed a fast CU partition algorithm based on predictive partition convolutional Neural Network (PP-CNN) . Firstly, this paper analyzed the partition characteristics of CUs of ERP 360-degree video in different latitude regions and introduced the latitude feature in thre propoed algorithm. Secondly, the algorithm established 360-degree video dataset with the characteristics of latitude and quantization parameters. Then, this method designed a lightweight PP-CNN model to predict the edge division information of CUs. Next, the algorithm based on the output of PP-CNN model developed a dual-threshold CU fast partition decision scheme to remove redundant partition patterns. Finally, this paper designed three decision modes, fast, balanced and performance according to the needs of coding scenarios. The extensive experimental results show that the proposed algorithm is able to shorten the coding time by 39.31%-61.95% on average under the full intra-frame coding configuration at the BDBR increases by only 0.37%-1.43% compared with the official testbed VTM-14.0-360lib13.1, indicating that the algorithm can realize faster coding speed under the premise of guaranteeing coding performance.

Foundation Support

国家自然科学基金资助项目(62371081)
重庆市自然科学基金(cstc2021jcyj-msxmX0411和CSTB2022NSCQ-MSX0873)
重庆理工大学科研创新团队(2023TDZ003)
重庆理工大学校级联合资助项目(gzlcx20243086)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.07.0350
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 5

Publish History

[2025-03-06] Accepted Paper

Cite This Article

向海, 陈芬, 秦裔清, 等. 基于预测划分卷积神经网络的全景视频快速编码算法 [J]. 计算机应用研究, 2025, 42 (5). (2025-03-06). https://doi.org/10.19734/j.issn.1001-3695.2024.07.0350. (Xiang Hai, Chen Fen, Qin Yiqing, et al. Fast coding algorithm based on predictive partition convolutional neural network for 360-degree video [J]. Application Research of Computers, 2025, 42 (5). (2025-03-06). https://doi.org/10.19734/j.issn.1001-3695.2024.07.0350. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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