CNN based optimal intra prediction mode estimation in video coding

Ryota Yokoyama; Masahiko Tahara; Masaru Takeuchi; Heming Sun; Yasutaka Matsuo; Jiro Katto

doi:10.1109/ICCE46568.2020.9043170

CNN based optimal intra prediction mode estimation in video coding

Ryota Yokoyama, Masahiko Tahara, Masaru Takeuchi, Heming Sun, Yasutaka Matsuo, Jiro Katto

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

The amount of video data is so large that efficient video compression is required for the storage and transmission. Intra prediction is one of important components in video compression. In this paper, we examine various Convolutional Neural Network (CNN) structures to estimate optimal intra prediction mode as Most Probable Modes (MPMs). Moreover, we investigate several combinations of the MPMs obtained by the CNN and MPMs derived from High Efficiency Video Coding Test Model (HM). From these experimental results, we find that using 6 MPMs from both CNN and HM with moderate number of channels or kernel size is preferred.

Original language	English
Title of host publication	2020 IEEE International Conference on Consumer Electronics, ICCE 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728151861
DOIs	https://doi.org/10.1109/ICCE46568.2020.9043170
Publication status	Published - 2020 Jan
Event	2020 IEEE International Conference on Consumer Electronics, ICCE 2020 - Las Vegas, United States Duration: 2020 Jan 4 → 2020 Jan 6

Publication series

Name	Digest of Technical Papers - IEEE International Conference on Consumer Electronics
Volume	2020-January
ISSN (Print)	0747-668X

Conference

Conference	2020 IEEE International Conference on Consumer Electronics, ICCE 2020
Country/Territory	United States
City	Las Vegas
Period	20/1/4 → 20/1/6

Keywords

Convolutional Neural Network (CNN)
Intra prediction
Video coding

ASJC Scopus subject areas

Industrial and Manufacturing Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/ICCE46568.2020.9043170

Cite this

Yokoyama, R., Tahara, M., Takeuchi, M., Sun, H., Matsuo, Y., & Katto, J. (2020). CNN based optimal intra prediction mode estimation in video coding. In 2020 IEEE International Conference on Consumer Electronics, ICCE 2020 Article 9043170 (Digest of Technical Papers - IEEE International Conference on Consumer Electronics; Vol. 2020-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE46568.2020.9043170

CNN based optimal intra prediction mode estimation in video coding. / Yokoyama, Ryota; Tahara, Masahiko; Takeuchi, Masaru et al.
2020 IEEE International Conference on Consumer Electronics, ICCE 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 9043170 (Digest of Technical Papers - IEEE International Conference on Consumer Electronics; Vol. 2020-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Yokoyama, R, Tahara, M, Takeuchi, M, Sun, H, Matsuo, Y & Katto, J 2020, CNN based optimal intra prediction mode estimation in video coding. in 2020 IEEE International Conference on Consumer Electronics, ICCE 2020., 9043170, Digest of Technical Papers - IEEE International Conference on Consumer Electronics, vol. 2020-January, Institute of Electrical and Electronics Engineers Inc., 2020 IEEE International Conference on Consumer Electronics, ICCE 2020, Las Vegas, United States, 20/1/4. https://doi.org/10.1109/ICCE46568.2020.9043170

Yokoyama R, Tahara M, Takeuchi M, Sun H, Matsuo Y, Katto J. CNN based optimal intra prediction mode estimation in video coding. In 2020 IEEE International Conference on Consumer Electronics, ICCE 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 9043170. (Digest of Technical Papers - IEEE International Conference on Consumer Electronics). doi: 10.1109/ICCE46568.2020.9043170

@inproceedings{8db77165ea004ff6a5e43716fb7e95bf,

title = "CNN based optimal intra prediction mode estimation in video coding",

abstract = "The amount of video data is so large that efficient video compression is required for the storage and transmission. Intra prediction is one of important components in video compression. In this paper, we examine various Convolutional Neural Network (CNN) structures to estimate optimal intra prediction mode as Most Probable Modes (MPMs). Moreover, we investigate several combinations of the MPMs obtained by the CNN and MPMs derived from High Efficiency Video Coding Test Model (HM). From these experimental results, we find that using 6 MPMs from both CNN and HM with moderate number of channels or kernel size is preferred.",

keywords = "Convolutional Neural Network (CNN), Intra prediction, Video coding",

author = "Ryota Yokoyama and Masahiko Tahara and Masaru Takeuchi and Heming Sun and Yasutaka Matsuo and Jiro Katto",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Consumer Electronics, ICCE 2020 ; Conference date: 04-01-2020 Through 06-01-2020",

year = "2020",

month = jan,

doi = "10.1109/ICCE46568.2020.9043170",

language = "English",

series = "Digest of Technical Papers - IEEE International Conference on Consumer Electronics",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2020 IEEE International Conference on Consumer Electronics, ICCE 2020",

}

TY - GEN

T1 - CNN based optimal intra prediction mode estimation in video coding

AU - Yokoyama, Ryota

AU - Tahara, Masahiko

AU - Takeuchi, Masaru

AU - Sun, Heming

AU - Matsuo, Yasutaka

AU - Katto, Jiro

PY - 2020/1

Y1 - 2020/1

N2 - The amount of video data is so large that efficient video compression is required for the storage and transmission. Intra prediction is one of important components in video compression. In this paper, we examine various Convolutional Neural Network (CNN) structures to estimate optimal intra prediction mode as Most Probable Modes (MPMs). Moreover, we investigate several combinations of the MPMs obtained by the CNN and MPMs derived from High Efficiency Video Coding Test Model (HM). From these experimental results, we find that using 6 MPMs from both CNN and HM with moderate number of channels or kernel size is preferred.

AB - The amount of video data is so large that efficient video compression is required for the storage and transmission. Intra prediction is one of important components in video compression. In this paper, we examine various Convolutional Neural Network (CNN) structures to estimate optimal intra prediction mode as Most Probable Modes (MPMs). Moreover, we investigate several combinations of the MPMs obtained by the CNN and MPMs derived from High Efficiency Video Coding Test Model (HM). From these experimental results, we find that using 6 MPMs from both CNN and HM with moderate number of channels or kernel size is preferred.

KW - Convolutional Neural Network (CNN)

KW - Intra prediction

KW - Video coding

UR - http://www.scopus.com/inward/record.url?scp=85082603510&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85082603510&partnerID=8YFLogxK

U2 - 10.1109/ICCE46568.2020.9043170

DO - 10.1109/ICCE46568.2020.9043170

M3 - Conference contribution

AN - SCOPUS:85082603510

T3 - Digest of Technical Papers - IEEE International Conference on Consumer Electronics

BT - 2020 IEEE International Conference on Consumer Electronics, ICCE 2020

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 IEEE International Conference on Consumer Electronics, ICCE 2020

Y2 - 4 January 2020 through 6 January 2020

ER -

CNN based optimal intra prediction mode estimation in video coding

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this