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Tree-Based Ensemble Methods for Complexity Reduction of VVC Intra Coding
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| The rise of new applications and emerging services required ultra-high definition (UHD) led to the development of a new video compression standard, name Versatile Video Coding (VVC). In comparison with High Efficiency Video Coding, the new standard increases the coding efficiency, at the expense of greatly increasing the computational complexity of the encoding process, especially in UHD and 360°video. To overcome this issue, this paper presents a novel method to reduce the computational complexity of intra-coded 360°video in Equirectangular Projection format, based on 3 tree-based ensemble models to predict the maximum partition depth that should be used for intra-coding of the complex nested data structures (Quad Tree, Binary Tree and Ternary Tree) used in the VVC standard. Two different tree-based ensemble methods are studied, namely Random Forest and Extremely Randomised Trees. The experimental results achieve, on average, complexity reductions of 56.25% and 57.45% for Random Forests and Extremely Randomised Trees methods, with small loss of coding efficiency of 1.37 % and 1.46 %, respectively. | 284.37 KB | Adobe PDF |
Orientador(es)
Resumo(s)
The rise of new applications and emerging services required ultra-high definition (UHD) led to the development of a new video compression standard, name Versatile Video Coding (VVC). In comparison with High Efficiency Video Coding, the new standard increases the coding efficiency, at the expense of greatly increasing the computational complexity of the encoding process, especially in UHD and 360°video. To overcome this issue, this paper presents a novel method to reduce the computational complexity of intra-coded 360°video in Equirectangular Projection format, based on 3 tree-based ensemble models to predict the maximum partition depth that should be used for intra-coding of the complex nested data structures (Quad Tree, Binary Tree and Ternary Tree) used in the VVC standard. Two different tree-based ensemble methods are studied, namely Random Forest and Extremely Randomised Trees. The experimental results achieve, on average, complexity reductions of 56.25% and 57.45% for Random Forests and Extremely Randomised Trees methods, with small loss of coding efficiency of 1.37 % and 1.46 %, respectively.
Descrição
EISBN - 978-1-6654-1588-0
Date of Conference: 11-12 February 2021
Date of Conference: 11-12 February 2021
Palavras-chave
omnidirectional video compression VVC 360- degree video complexity reduction
Contexto Educativo
Citação
J. N. Filipe, J. Carreira, L. M. N. Tavora, S. M. M. de Faria, A. Navarro and P. A. A. Assuncao, "Tree-Based Ensemble Methods for Complexity Reduction of VVC Intra Coding," 2021 Telecoms Conference (ConfTELE), Leiria, Portugal, 2021, pp. 1-6, doi: https://doi.org/10.1109/ConfTELE50222.2021.9435476.
Editora
IEEE Canada
Licença CC
Sem licença CC