A fast 3D-HEVC video encoding algorithm based on Bayesian decision

Xiaolan Wang

doi:10.1117/12.3011506

7 December 2023 A fast 3D-HEVC video encoding algorithm based on Bayesian decision

Xiaolan Wang

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 129413Q (2023) https://doi.org/10.1117/12.3011506
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

In order to improve the encoding performance of 3D videos, the 3D-HEVC encoding standard has also added new stereo video encoding technologies such as interview prediction and depth map encoding. However, excellent encoding performance is achieved through significant computational complexity. In order to reduce the computational complexity of the 3D-HEVC encoding process, this paper proposes a 3D-HEVC fast encoding algorithm based on Bayesian decision-making. This algorithm uses machine learning methods to extract features that meet specific relationships and uses these features to learn and establish classification and prediction models. The experimental results show that compared with traditional 3D-HEVC encoding algorithms, the machine learning method based on Bayesian decision-making can effectively improve the video coding performance of 3D-HEVC, with a reduction of 23.28% in total encoding time and 39.09% in deep mapping encoding time, respectively.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaolan Wang "A fast 3D-HEVC video encoding algorithm based on Bayesian decision", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 129413Q (7 December 2023); https://doi.org/10.1117/12.3011506

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KEYWORDS

Video coding

Video

Copper

Depth maps

Video compression

3D video compression

Machine learning

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