A Content-Based Optimization of Data Stream Television Multiplex
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A Content-Based Optimization of Data Stream Television Multiplex

Authors: Jaroslav Polec, Martin Šimek, Michal Martinovič, Elena Šikudová

Abstract:

The television multiplex has reserved capacity and therefore we can use only limited number of videos for propagation of it. Appropriate composition of the multiplex has a major impact on how many videos is spread by multiplex. Therefore in this paper is designed a simple algorithm to optimize capacity utilization multiplex. Significant impact on the number of programs in the multiplex has also the fact from which programs is composed. Content of multiplex can be movies, news, sport, animated stories, documentaries, etc. These types have their own specific characteristics that affect their resulting data stream. In this paper is also done an impact analysis of the composition of the multiplex to use its capacity by video content. 

Keywords: Multiplex, content, group of pictures, frame, capacity.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1088238

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References:


[1] TechnischeUniversitätMünchen, Institute for Data Processing, TUM Multi Format Test Set. (Online). Available: www.ldv.ei.tum.de/videolab, 2011.
[2] Video sequences are owned by NTIA/ITS, an agency of the U.S. Federal Government, Project Number 3141012-300, Video Quality Research, 2008.
[3] Blender Foundation / Netherlands Media Art Institute Available: www.elephantsdream.org, 2006.
[4] Blender Foundation / www.bigbuckbunny.org, 2008.
[5] EN 300 429 V1.2.1,Digital Video Broadcasting (DVB); Framing structure, channel coding and modulation for cable systems, European Broadcasting Union, ETSI, Sophia AntipolisCedex, April 1998.
[6] Balakrishnan, M., Cohen, R., "Global Optimization of Multiplexed Video Encoders", Proceeding ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97). Vol. 1., Santa Barbara 1997, pp. 377 - 380.
[7] Hoang, D.T., Vitter, J.S., "Multiplexing Vbr Video Sequences Onto A CBR Channel With Lexicographic Optimization", Proceeding ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97). Vol. 1., Santa Barbara 1997, pp. 369 - 372.
[8] He, Z., Wu, D.O., ‘‘Linear Rate Control and Optimum Statistical Multiplexing for H.264 Video Broadcast", IEEE Trans. Multimedia, vol. 10, no. 7, pp. 1237–1249, 2008.
[9] Changuel, N., Sayadi, B., Kieffer, M., ‘‘Predictive Control for Efficient Statistical Multiplexing of Digital Video Programs’’, in Proc. IEEE Int. Packet Video Workshop, 2009, pp. 1–9.
[10] Changuel, N., Sayadi, B., Kieffer, M.,“Statistical Multiplexing of Video Programs”,IEEE Vehicular Technolology Magazine, September 2009, pp. 62 - 68.
[11] Moiron, S., Razavi, R., Fleury, M.,Ghanbari, M.,“Statistical Multiplexing of Transcoded IPTV Streams Based on Content Complexity”, Mobile Multimedia Communications, Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Vol. 77, Springer 2012, pp 60-73.
[12] Kocisky, M., Vargic, R., Kotuliak, I., "Wavelet-domain based estimation of self-similarity in signals", in Proceeding of RTT 2006, pp. 441-444.
[13] Šikudová, E.,Possibilities of Automatic Image Data Classification, PhD. Thesis, UK Bratislava, 2006.
[14] Atrey, Pradeep, K., Anwar, M.:“Multimodal fusion for multimedia analysis”, Multimedia systems,vol. 16, Springer-Verlag 2010, pp. 345- 379.
[15] Gulen, Elvan, Turgay, Y., Yazici. A. “Multimodal Information Fusion for Semantic Video Analysis”, International Journal of Multimedia Data Engineering and Management (IJMDEM) 3.4, 2012, pp. 52-74.
[16] Smeaton, A. F., Wessel Kraaij, P. O.:” High-Level Feature Detection from Video inTRECVid: a 5-Year Retrospective of Achievements”, Published in A. Divakaran (ed.), Multimedia Content Analysis, Signals and CommunicationTechnology, DOI 10.1007/978-0-387-76569-3 6, SpringerScience+BusinessMedia, LLC 2009, pp. 151-174.
[17] Smeaton, A. F., Over, P., Doherty, A.R.,”Video shot boundary detection: Seven years of TRECVid activity”,Computer Vision and Image Understanding, vol. 114, 2010, pp. 411-418.