COMPRESSION OF 3D POINT CLOUDS USING 1D DISCRETE COSINE TRANSFORM

Shuai Gu; Junhui Hou; Huanqiang Zeng; Jing Chen; Jianqing Zhu; Kai-Kuang Ma

doi:10.1109/ispacs.2017.8266472

COMPRESSION OF 3D POINT CLOUDS USING 1D DISCRETE COSINE TRANSFORM

Shuai Gu
, Junhui Hou
, Huanqiang Zeng^*
, Jing Chen
, Jianqing Zhu
, Kai-Kuang Ma

^*Corresponding author for this work

Department of Computer Science

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

5 Citations (Scopus)

Abstract

Discrete cosine transform is an ideal method to decorrelate the signal. In this paper, we proposed a novel entropy coding based on 1D-DCT to compress the 3D point clouds. Different from the former method which is based on Laplacian distribution, we encoding the coefficients by count the nonzero coefficients. We count the number, index, value of the nonzero coefficients of each block and then use arithmetic encoder to compress the coefficient. Experimental results on a number of point clouds show our method is more efficient than the former method based on DCT.

Original language	English
Title of host publication	2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)
Publisher	IEEE
Pages	196-200
ISBN (Electronic)	9781538621592
DOIs	https://doi.org/10.1109/ispacs.2017.8266472
Publication status	Published - Nov 2017
Event	25th IEEE International Symposium on Intelligent Signal Processing and Communication Systems 2017 (ISPACS 2017) - Wanda Realm Xiamen North Bay Hotel, Xiamen, China Duration: 6 Nov 2017 → 9 Nov 2017 Conference number: 25th http://ispacs2017.hqu.edu.cn/

Publication series

Name	IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)
Publisher	IEEE

Conference

Conference	25th IEEE International Symposium on Intelligent Signal Processing and Communication Systems 2017 (ISPACS 2017)
Abbreviated title	ISPACS2017
Place	China
City	Xiamen
Period	6/11/17 → 9/11/17
Internet address	http://ispacs2017.hqu.edu.cn/

Research Keywords

Discrete cosine transform
entropy coding
3D point cloud
nonzero coefficients
index
MESH COMPRESSION

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10.1109/ispacs.2017.8266472

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Gu, S., Hou, J., Zeng, H., Chen, J., Zhu, J., & Ma, K.-K. (2017). COMPRESSION OF 3D POINT CLOUDS USING 1D DISCRETE COSINE TRANSFORM. In 2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) (pp. 196-200). (IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)). IEEE. https://doi.org/10.1109/ispacs.2017.8266472

@inproceedings{00e0006f3d8d4ab9bbaf7f47e1ebfe39,

title = "COMPRESSION OF 3D POINT CLOUDS USING 1D DISCRETE COSINE TRANSFORM",

abstract = "Discrete cosine transform is an ideal method to decorrelate the signal. In this paper, we proposed a novel entropy coding based on 1D-DCT to compress the 3D point clouds. Different from the former method which is based on Laplacian distribution, we encoding the coefficients by count the nonzero coefficients. We count the number, index, value of the nonzero coefficients of each block and then use arithmetic encoder to compress the coefficient. Experimental results on a number of point clouds show our method is more efficient than the former method based on DCT.",

keywords = "Discrete cosine transform, entropy coding, 3D point cloud, nonzero coefficients, index, MESH COMPRESSION",

author = "Shuai Gu and Junhui Hou and Huanqiang Zeng and Jing Chen and Jianqing Zhu and Kai-Kuang Ma",

year = "2017",

month = nov,

doi = "10.1109/ispacs.2017.8266472",

language = "English",

series = "IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)",

publisher = "IEEE",

pages = "196--200",

booktitle = "2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)",

address = "United States",

note = "25th IEEE International Symposium on Intelligent Signal Processing and Communication Systems 2017 (ISPACS 2017), ISPACS2017 ; Conference date: 06-11-2017 Through 09-11-2017",

url = "http://ispacs2017.hqu.edu.cn/",

}

Gu, S, Hou, J, Zeng, H, Chen, J, Zhu, J & Ma, K-K 2017, COMPRESSION OF 3D POINT CLOUDS USING 1D DISCRETE COSINE TRANSFORM. in 2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS). IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), IEEE, pp. 196-200, 25th IEEE International Symposium on Intelligent Signal Processing and Communication Systems 2017 (ISPACS 2017), Xiamen, China, 6/11/17. https://doi.org/10.1109/ispacs.2017.8266472

COMPRESSION OF 3D POINT CLOUDS USING 1D DISCRETE COSINE TRANSFORM. / Gu, Shuai; Hou, Junhui; Zeng, Huanqiang et al.
2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS). IEEE, 2017. p. 196-200 (IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - COMPRESSION OF 3D POINT CLOUDS USING 1D DISCRETE COSINE TRANSFORM

AU - Gu, Shuai

AU - Hou, Junhui

AU - Zeng, Huanqiang

AU - Chen, Jing

AU - Zhu, Jianqing

AU - Ma, Kai-Kuang

N1 - Conference code: 25th

PY - 2017/11

Y1 - 2017/11

N2 - Discrete cosine transform is an ideal method to decorrelate the signal. In this paper, we proposed a novel entropy coding based on 1D-DCT to compress the 3D point clouds. Different from the former method which is based on Laplacian distribution, we encoding the coefficients by count the nonzero coefficients. We count the number, index, value of the nonzero coefficients of each block and then use arithmetic encoder to compress the coefficient. Experimental results on a number of point clouds show our method is more efficient than the former method based on DCT.

AB - Discrete cosine transform is an ideal method to decorrelate the signal. In this paper, we proposed a novel entropy coding based on 1D-DCT to compress the 3D point clouds. Different from the former method which is based on Laplacian distribution, we encoding the coefficients by count the nonzero coefficients. We count the number, index, value of the nonzero coefficients of each block and then use arithmetic encoder to compress the coefficient. Experimental results on a number of point clouds show our method is more efficient than the former method based on DCT.

KW - Discrete cosine transform

KW - entropy coding

KW - 3D point cloud

KW - nonzero coefficients

KW - index

KW - MESH COMPRESSION

UR - https://www.scopus.com/pages/publications/85047462099

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85047462099&origin=recordpage

U2 - 10.1109/ispacs.2017.8266472

DO - 10.1109/ispacs.2017.8266472

M3 - RGC 32 - Refereed conference paper (with host publication)

T3 - IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

SP - 196

EP - 200

BT - 2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

PB - IEEE

T2 - 25th IEEE International Symposium on Intelligent Signal Processing and Communication Systems 2017 (ISPACS 2017)

Y2 - 6 November 2017 through 9 November 2017

ER -

COMPRESSION OF 3D POINT CLOUDS USING 1D DISCRETE COSINE TRANSFORM

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