Joint texture and depth map coding for error-resilient 3-D video transmission

Pan Gao; Wei Xiang; D.M. Motiur Rahaman; Manoranjan Paul

doi:10.1109/ICIP.2017.8296613

Joint texture and depth map coding for error-resilient 3-D video transmission

Pan Gao, Wei Xiang, D.M. Motiur Rahaman, Manoranjan Paul

Research output: Book chapter/Published conference paper › Conference paper › peer-review

1 Citation (Scopus)

Abstract

This paper addresses the problem of error-resilient source coding for 3-D video transmission over packet-loss networks. The proposed approach jointly optimizes the texture coding mode and the depth coding mode for each macroblock in the reference views. Firstly, a distortion model is developed to capture the effect of the texture distortion and depth distortion on the synthesized view. Then, joint optimization of texture and depth coding modes is derived based upon an operational rate-distortion framework using Lagrange multiplier method. In particular, a dual trellis-based algorithm is introduced in order to overcome the macroblock interdependencies of texture and depth map in the optimization procedure. Simulation results demonstrate that significant and consistent gains can be achieved over currently used techniques.

Original language	English
Title of host publication	2017 IEEE International Conference on Image Processing
Subtitle of host publication	Proceedings
Place of Publication	United States
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	1905-1909
Number of pages	5
ISBN (Electronic)	9781509021758
ISBN (Print)	9781509021765 (Print on demand)
DOIs	https://doi.org/10.1109/ICIP.2017.8296613
Publication status	Published - 22 Feb 2018
Event	2017 24th IEEE International Conference on Image Processing: ICIP 2017 - China National Convention Center , Beijing, China Duration: 17 Sept 2017 → 20 Sept 2017 http://2017.ieeeicip.org/ (Conference website)

Conference

Conference	2017 24th IEEE International Conference on Image Processing
Country/Territory	China
City	Beijing
Period	17/09/17 → 20/09/17
Other	The 24th IEEE International Conference on Image Processing (ICIP) will be held in the China National Conventional Center, Beijing, China, on September 17-20, 2017. ICIP is the world' largest and most comprehensive technical conference focused on image and video processing and computer vision. The conference will feature world-class speakers, tutorials, exhibits, and a vision technology showcase.
Internet address	http://2017.ieeeicip.org/ (Conference website)

Access to Document

10.1109/ICIP.2017.8296613

Cite this

@inproceedings{72b21eb63f6a48888ef1036b27feefb0,

title = "Joint texture and depth map coding for error-resilient 3-D video transmission",

abstract = "This paper addresses the problem of error-resilient source coding for 3-D video transmission over packet-loss networks. The proposed approach jointly optimizes the texture coding mode and the depth coding mode for each macroblock in the reference views. Firstly, a distortion model is developed to capture the effect of the texture distortion and depth distortion on the synthesized view. Then, joint optimization of texture and depth coding modes is derived based upon an operational rate-distortion framework using Lagrange multiplier method. In particular, a dual trellis-based algorithm is introduced in order to overcome the macroblock interdependencies of texture and depth map in the optimization procedure. Simulation results demonstrate that significant and consistent gains can be achieved over currently used techniques.",

keywords = "Texture coding mode, Depth coding mode, Error-resilient coding, 3-D video transmission",

author = "Pan Gao and Wei Xiang and Rahaman, {D.M. Motiur} and Manoranjan Paul",

note = "Includes bibliographical references.; 2017 24th IEEE International Conference on Image Processing : ICIP 2017 ; Conference date: 17-09-2017 Through 20-09-2017",

year = "2018",

month = feb,

day = "22",

doi = "10.1109/ICIP.2017.8296613",

language = "English",

isbn = "9781509021765 (Print on demand)",

pages = "1905--1909",

booktitle = "2017 IEEE International Conference on Image Processing",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States",

url = "http://2017.ieeeicip.org/",

}

Gao, P, Xiang, W, Rahaman, DMM & Paul, M 2018, Joint texture and depth map coding for error-resilient 3-D video transmission. in 2017 IEEE International Conference on Image Processing: Proceedings., 8296613, IEEE, Institute of Electrical and Electronics Engineers, United States, pp. 1905-1909, 2017 24th IEEE International Conference on Image Processing, Beijing, China, 17/09/17. https://doi.org/10.1109/ICIP.2017.8296613

Joint texture and depth map coding for error-resilient 3-D video transmission. / Gao, Pan; Xiang, Wei; Rahaman, D.M. Motiur et al.
2017 IEEE International Conference on Image Processing: Proceedings. United States: IEEE, Institute of Electrical and Electronics Engineers, 2018. p. 1905-1909 8296613.

Research output: Book chapter/Published conference paper › Conference paper › peer-review

TY - GEN

T1 - Joint texture and depth map coding for error-resilient 3-D video transmission

AU - Gao, Pan

AU - Xiang, Wei

AU - Rahaman, D.M. Motiur

AU - Paul, Manoranjan

N1 - Includes bibliographical references.

PY - 2018/2/22

Y1 - 2018/2/22

N2 - This paper addresses the problem of error-resilient source coding for 3-D video transmission over packet-loss networks. The proposed approach jointly optimizes the texture coding mode and the depth coding mode for each macroblock in the reference views. Firstly, a distortion model is developed to capture the effect of the texture distortion and depth distortion on the synthesized view. Then, joint optimization of texture and depth coding modes is derived based upon an operational rate-distortion framework using Lagrange multiplier method. In particular, a dual trellis-based algorithm is introduced in order to overcome the macroblock interdependencies of texture and depth map in the optimization procedure. Simulation results demonstrate that significant and consistent gains can be achieved over currently used techniques.

AB - This paper addresses the problem of error-resilient source coding for 3-D video transmission over packet-loss networks. The proposed approach jointly optimizes the texture coding mode and the depth coding mode for each macroblock in the reference views. Firstly, a distortion model is developed to capture the effect of the texture distortion and depth distortion on the synthesized view. Then, joint optimization of texture and depth coding modes is derived based upon an operational rate-distortion framework using Lagrange multiplier method. In particular, a dual trellis-based algorithm is introduced in order to overcome the macroblock interdependencies of texture and depth map in the optimization procedure. Simulation results demonstrate that significant and consistent gains can be achieved over currently used techniques.

KW - Texture coding mode

KW - Depth coding mode

KW - Error-resilient coding

KW - 3-D video transmission

UR - http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8267582

UR - http://2017.ieeeicip.org/

UR - http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8296229

U2 - 10.1109/ICIP.2017.8296613

DO - 10.1109/ICIP.2017.8296613

M3 - Conference paper

SN - 9781509021765 (Print on demand)

SP - 1905

EP - 1909

BT - 2017 IEEE International Conference on Image Processing

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - United States

T2 - 2017 24th IEEE International Conference on Image Processing

Y2 - 17 September 2017 through 20 September 2017

ER -

Joint texture and depth map coding for error-resilient 3-D video transmission

Abstract

Conference

Access to Document

Other files and links

Fingerprint

Cite this