More Web Proxy on the site http://driver.im/

research-article

A cognitive approach for effective coding and transmission of 3D video

Authors:

Giancarlo CalvagnoAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 7S, Issue 1

Article No.: 23, Pages 1 - 21

https://doi.org/10.1145/2037676.2037680

Published: 04 November 2011 Publication History

Abstract

Future multimedia applications will rely on the transmission of 3D video contents within heterogeneous fruition scenarios, and as a matter of fact, the reliable delivery of 3D video signals proves to be a crucial issue in such communications. To this purpose, multimedia communication experts have been designing cross-layer strategies to improve the quality of the perceived 3D experience. This article presents a new cross-layer strategy, called Cognitive Source Coding (CSC), that defines a new 3D video system able to identify the different elements of the 3D scene and choose the most appropriate coding strategy.

References

[1]

Aaron, A., Zhang, R., and Girod, B. 2002. Wyner-ziv coding for motion video. In Proceedings of the Asilomar Conference on Signals, Systems and Computers. Vol. 1. 240--244.

[2]

Adikari, A. B. B., Fernando, W. A. C., Weerakkody, W. A. R. J., Kondoz, A., Martínez, J. L., and Cuenca, P. 2008. DVC based stereoscopic video transmission in a mobile communication system. In Proceedings of the IEEE Future Multimedia Networking (FMN). (co-located with NGMAST'08). 439--443.

Digital Library

[3]

Aksay, A., Bilen, C., Kurutepe, E., Ozcelebi, T., Akar, G. B., Civanlar, R., and Tekalp, M. 2006. Temporal and spatial scaling for stereoscopic video compression. In Proceedings of the European Signal Processing Conference (EUSIPCO).

[4]

Alregib, G., Altunbasak, Y., and Rossignac, J. 2005. Error-resilient transmission of 3d models. ACM Trans. Graph. 24, 2, 182--208.

Digital Library

[5]

Artigas, X., Ascenso, J., Dalai, M., Klomp, S., Kubasov, D., and Ouaret, M. 2007. The DISCOVER codec: Architecture, techniques and evaluation. In Proceedings of the Picture Coding Symposium (PCS).

[6]

Balter, R., Gioia, P., and Morin, L. 2006. Scalable and efficient coding using 3D modeling. IEEE Trans. Multimedia 8, 6, 1147--1155.

Digital Library

[7]

Benoit, A., Callet, P. L., Campisi, P., and Cousseau, R. 2008. Quality assessment of stereoscopic images. EURASIP J. Image Video Process. ID 659024.

[8]

Boser, B. E., Guyon, I. M., and Vapnik, V. N. 1992. A training algorithm for optimal margin classifiers. In Proceedings of the 5^th Annual ACM Workshop on Computational Learning Theory (COLT). 144--152.

Digital Library

[9]

Boughorbel, S., Tarel, J. P., and Boujemaa, N. 2005. Conditionally positive definite kernels for SVM based image recognition. In Proceedings of the IEEE International Conference on Multimedia and Expo (ICME). 113--116.

[10]

Bremond, R., Petit, J., and Tarel, J.-P. 2010. Saliency maps of high dynamic range images. In Proceedings of the Media Retargeting Workshop in conjunction with ECCV'10. http://perso.lcpc.fr/tarel.jean-philippe/publis/weccv10.html.

Digital Library

[11]

Crave, O., Guillemot, C., Pesquet-Popescu, B., and Tillier, C. 2008. Multiple description source coding with side information. In Proceedings of the European Signal Processing Conference (EUSIPCO).

[12]

Fan, Y., Wang, J., Sun, J., Wang, P., and Yu, S. 2003. A novel multiple description video codec based on Slepian-Wolf coding. In Proceedings of the Data Compression Conference (DCC). 515.

Digital Library

[13]

Färber, N., Stuhlmuller, K., and Girod, B. 1999. Analysis of error propagation in hybrid video coding with application to error resilience. In Proceedings of the International Conference on Image Processing, (ICIP). 550--554.

[14]

Fehn, C. 2004. 3D-TV Using depth-image-based rendering (DIBR). In Proceedings of the Picture Coding Symposium (PCS).

[15]

Felzenszwalb, P. F. and Huttenlocher, D. P. 2004. Efficient graph-based image segmentation. Int. J. Computer Vision 59, 2, 167--181.

Digital Library

[16]

Fraunhofer HHI. 2011. Repository of FHG HHI on 3DTV NoE. https://www.3dtv-research.org/3dav/3DAV_Demos/FHG_HHI/Sequences/.

[17]

Goel, S., Ismael, Y., and Boyoumi, M. A. 2005. Adaptive search window size algorithm for fast motion estimation in H.264/AVC standard. In Proceedings of the IEEE International Midwest Symposium on Circuits and Systems (MWSCAS). 1557--1560.

[18]

Goyal, V. K. 2001. Multiple description coding: compression meets the network. IEEE Signal Process. Mag. 8, 5, 74--93.

[19]

Haykin, S. 2005. Cognitive radio: Brain-empowered wireless communications. IEEE J. Sel. Areas Comm. 23, 2, 201--220. (Invited).

Digital Library

[20]

ISO/IEC JTC1. 2001. Coding of audio-visual objects - Part 2: Visual. ISO/IEC 14 496-2 (MPEG-4 Visual version 1), 4/99; Amendment 1 (version 2), 2/00; Amendment 4 (streaming profile), 1/01.

[21]

ITU-T. 1995. Video coding for low bitrate communications, Version 1. ITU-T Recommendation H.263.

[22]

ITU-T and ISO/IEC JTC1. 1994. Generic coding of moving pictures and associated audio information - Part 2: Video. ITU-T Recommendation H.262-ISO/IEC 13 818-2 (MPEG-2).

[23]

Jagmohan, A. and Ahuja, N. 2003. Wyner-Ziv encoded predictive multiple descriptions. In Proceedings of the Data Compression Conference (DCC). 213--222.

Digital Library

[24]

Karim, H. A., Hewage, C. T. E. R., Yu, A. C., Worral, S., Dogan, S., and Kondoz, A. M. 2007. Scalable multiple description 3D video coding based on even and odd frame. In Proceedings of the Pretante Coding Symposium (PCS).

[25]

Katsaggelos, A. K., Eisenberg, Y., Zhai, F., Berry, R., and Pappas, T. N. 2005. Advances in efficient resource allocation for packet-based real-time video transmission. Proc. IEEE 93, 1, 135--147.

[26]

Liao, J. and Villasenor, J. 2000. Adaptive intra block update for robust transmission of H.263. IEEE Trans. Circuits Syst. Video Technol. 10, 1, 30--35.

Digital Library

[27]

Microsoft Research. 2011. MSR 3D video. http://research.microsoft.com/en-us/um/people/sbkang/3dvideodownload.

[28]

Milani, S. 2010. Simone Milani's Homepage. http://www.dei.unipd.it/~sim1mil/downloads.html.

[29]

Milani, S. 2011. Simone Milani's Homepage. http://www.dei.unipd.it/~sim1mil/publications.html&sharp;CSCDemo.

[30]

Milani, S. and Calvagno, G. 2009. A distributed video coding approach for multiple description video transmission over lossy channels. In Proceedings of the European Signal Processing Conference (EUSIPCO). 1824--1828.

[31]

Milani, S. and Calvagno, G. 2010a. A cognitive approach for effective coding and transmission of 3D video. In Proceedings of the ACM Multimedia 2010.

Digital Library

[32]

Milani, S. and Calvagno, G. 2010b. A cognitive source coding scheme for multiple description 3DTV transmission. In Proceedings of the 11th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS'10).

[33]

Milani, S. and Calvagno, G. 2010c. Multiple description distributed video coding using redundant slices and lossy syndromes. IEEE Sig. Process. Lett. 17, 1, 51--54.

[34]

Mobile3DTV project. 2011. 3D Video database. http://sp.cs.tut.fi/mobile3dtv/stereo-video/.

[35]

Norkin, A., Aksay, A., Bilen, C., Akar, G. B., Gotchev, A., and Astola, J. 2006. Schemes for multiple description coding of stereoscopic 3D. In Proceedings of the Symposium on Multimedia Content Representation, Classification and Security. Lecture Notes in Computer Science, vol. 4105/2006. Springer, 730--737.

Digital Library

[36]

Puri, R. and Ramchandran, K. 2002. PRISM: A new robust video coding architecture based on distributed compression principles. In Proceedings of the Allerton Conference 2002. 402--408.

[37]

Reusens, E., Castagno, R., Buhan, C. L., Piron, L., Ebrahimi, T., and Kunt, M. 1996. Dynamic video coding—an overview. In Proceedings of the IEEE International Conference on Image Processing (ICIP). 377--380.

[38]

Rosenberg, J. and Schulzrinne, H. 1999. An RTP payload format for generic forward error correction (RFC2733). Internet Draft, Network Working Group.

Digital Library

[39]

Saxena, A., Sun, M., and Ng, A. Y. 2009. Make3D: Learning 3D scene structure from a single still image. IEEE Trans. Pattern Anal. Mach. Intell. 30, 5, 824--840.

Digital Library

[40]

Schierl, T., Stockhammer, T., and Wiegand, T. 2007. Compression of multiple depth maps for DIBR. IEEE Trans. Circuits Syst. Video Technol. 17, 9, 1204--1217.

Digital Library

[41]

Schulzrinne, H., Casner, S., Frederick, R., and Jacobson, V. 1996. RTP: A transport protocol for real-time applications (RFC1889). In Network Working Group.

[42]

Shi, S., Jeon, W., Nahrsted, K., and Campbell, R. 2009. M-TEEVE: Real-Time 3D video interaction and broadcasting framework for mobile devices. In Proceedings of the 2nd International Conference on Immersive Telecommunications (IMMERSCOM'09).

Digital Library

[43]

Wang, A., Zhao, Y., and Bai, H. 2009. Robust description distributed video coding using optimized zero-padding. Sci. China Ser. F-Inf. Sci. 52, 2, 206--214.

[44]

Wang, J., Wu, X., Yu, S., and Sun, J. 2006. Multiple descriptions in the Wyner-Ziv setting. In Proceedings of the IEEE Internet Symposium on Information Theory (ISIT). 1584--1588.

[45]

Wang, Z., Bovik, A. C., Sheikh, H. R., and Simoncelli, E. P. 2004. Image Quality Assessment: From Error Visibility to Structural Similarity. IEEE Trans. Image Process. 13, 4, 600--612.

Digital Library

[46]

Wiegand, T. 2004. Version 3 of H.264/AVC. In Proceedings of the 12th JVT Meeting.

[47]

Wu, M., Vetro, A., and Chen, C. W. 2004. Multiple Description Image Coding with Distributed Source Coding and Side Information. In Proceedings of SPIE: Multimedia Systems and Applications VII. Vol. 5600. 120--127.

[48]

Yeo, C. and Ramchandran, K. 2007. Robust distributed multiview video compression for wireless camera networks. In Proceedings of the IEEE Visual Communications and Image Processing (VCIP 2007). Vol. 6508. 65080P-1--65080P-9.

Cited By

Mari DCamuffo EMilani S(2023)CACTUS: Content-Aware Compression and Transmission Using Semantics for Automotive LiDAR DataSensors10.3390/s2312561123:12(5611)Online publication date: 15-Jun-2023
https://doi.org/10.3390/s23125611
Nousias SArvanitis GLalos AMoustakas K(2023)Deep Saliency Mapping for 3D Meshes and ApplicationsACM Transactions on Multimedia Computing, Communications, and Applications10.1145/355007319:2(1-22)Online publication date: 6-Feb-2023
https://doi.org/10.1145/3550073
Calemme MZanuttigh PMilani SCagnazzo MPesquet-Popescu B(2016)Depth map coding with elastic contours and 3D surface prediction2016 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP.2016.7532529(1106-1110)Online publication date: Sep-2016
https://doi.org/10.1109/ICIP.2016.7532529
Show More Cited By

Index Terms

A cognitive approach for effective coding and transmission of 3D video
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Image and video acquisition
        3D imaging
  2. Computer graphics
    1. Image compression
2. Information systems
  1. World Wide Web
    1. Web applications
      1. Internet communications tools
        Web conferencing

Recommendations

A cognitive approach for effective coding and transmission of 3D video
MM '10: Proceedings of the 18th ACM international conference on Multimedia

Reliable delivery of 3D video contents to a wide set of users is expected to be the next big revolution in multimedia applications provided that it is possible to grant a certain level of Quality-of-Experience (QoE) to the end user.

During the last ...
Conditional Entropy Coding of VQ Indexes for Image Compression
DCC '97: Proceedings of the Conference on Data Compression

Vector quantization (VQ) is a source coding methodology with provable rate-distortion optimality. However, despite more than two decades of intensive research, VQ theoretical promise is yet to be fully realized in image compression practice. Restricted ...
SSIM-based joint-bit allocation for 3D video coding

The quality of a 3D video display depends on virtual view synthesis process which is affected by the bit allocation criterion. The performance of a bit allocation algorithm is dependent on various encoding parameters like quantization parameter, motion ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 7S, Issue 1

Special section on ACM multimedia 2010 best paper candidates, and issue on social media

October 2011

246 pages

ISSN:1551-6857

EISSN:1551-6865

DOI:10.1145/2037676

Issue’s Table of Contents

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 November 2011

Accepted: 01 May 2011

Revised: 01 May 2011

Received: 01 January 2011

Published in TOMM Volume 7S, Issue 1

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

6
Total Citations
View Citations
340
Total Downloads

Downloads (Last 12 months)2
Downloads (Last 6 weeks)0

Reflects downloads up to 14 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Mari DCamuffo EMilani S(2023)CACTUS: Content-Aware Compression and Transmission Using Semantics for Automotive LiDAR DataSensors10.3390/s2312561123:12(5611)Online publication date: 15-Jun-2023
https://doi.org/10.3390/s23125611
Nousias SArvanitis GLalos AMoustakas K(2023)Deep Saliency Mapping for 3D Meshes and ApplicationsACM Transactions on Multimedia Computing, Communications, and Applications10.1145/355007319:2(1-22)Online publication date: 6-Feb-2023
https://doi.org/10.1145/3550073
Calemme MZanuttigh PMilani SCagnazzo MPesquet-Popescu B(2016)Depth map coding with elastic contours and 3D surface prediction2016 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP.2016.7532529(1106-1110)Online publication date: Sep-2016
https://doi.org/10.1109/ICIP.2016.7532529
Zhang LDong HSaddik A(2015)From 3D Sensing to PrintingACM Transactions on Multimedia Computing, Communications, and Applications10.1145/281871012:2(1-23)Online publication date: 20-Oct-2015
https://dl.acm.org/doi/10.1145/2818710
Debono CEllul G(2014)Evaluation of Long Term Evolution Cellular Network Performance when Transmitting Multi-view Video ContentInternational Journal of Wireless Networks and Broadband Technologies10.4018/ijwnbt.20140701023:3(16-32)Online publication date: 1-Jul-2014
https://doi.org/10.4018/ijwnbt.2014070102
Milani SCalvagno G(2012)Reliable 3D video P2P transmission enabling synthesis of virtual views2012 5th International Symposium on Communications, Control and Signal Processing10.1109/ISCCSP.2012.6217766(1-4)Online publication date: May-2012
https://doi.org/10.1109/ISCCSP.2012.6217766

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Issue’s Table of Contents