Abstract
We propose a transmission rate prediction method of video data. The proposed method uses a Kalman filter for predicting transmission rate. It used algorithm to detect shot transition information by high speed in compressed domain in order to grasp precise shot transition of video data and classified into abrupt shot transition type and gradual shot transition type. Classified information is used as factors of Kalman filter and to predict transmission rate of video data. It predicted transmission rate with 96.2 ~ 97.6% in the experiment.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
ISO/IEC JTC1/SC29/WG11, Information Technology- Coding of Moving Pictures and Associated Audio for Digital Storage Media at up to about 1.5Mbit/s, International Standard 11172 Part 1 - Part 5 (1993)
ISO/IEC JTC1/SC29/WG11, Information Technology- Generic Coding of Moving Pictures and Associated Audio Information, International Standard 13818 Part 1 ~ Part 5 (1996)
ISO/IEC JTC1/SC29/WG11, Multimedia Content Subscription Interface, Final Draft International Standard N4674 Part 1~Part 8 (2002)
Son, S.H., Koh, K.: VBR video data retrieval for video server. KISS Transaction A 25(2), 101–113 (1998)
Habib, I., Saadawi, T.: Dynamic bandwidth control in ATM networks. Compter Communications, 22 (1999)
Tsang, D.H.K., Bensaou, B., Lam, S.T.C.: Fuzzy-Based Rate Control for Real-Time MPEG Video. IEEE Transactions on Fuzzy System 6(4) (November 1998)
Piackering, M.R., Arnold, J.F.: A Perceptually Efficient VBR Rate Control Algorithm. IEEE Transactions on Image Processing, 3(5) (September 1994)
Heyman, D.P., Lakshman, T.: Source models for VBR broadcast-video traffic. IEEE/ACM Trans. Networking 4, 40–48 (1996)
Reibman, A.R., Haskell, B.: Constraints on variable bit rate video for ATM networks. IEEE Trans. Circuits Syst. Video Technol. 2, 361–372 (1992)
Heeke, H.: A traffic control algorithm for ATM networks. IEEE Trans. Circuits Syst. Video Technol. 3, 182–189 (1993)
Coelho, R., Tohme, S.: Video coding mechanism to predict video traffic in ATM network. In: IEEE GLOBECOM 1993, Houston, TX, December 1993, pp. 447–451 (1993)
Pickering, M.R., Arnold, J.F.: A perceptually efficient VBR rate control algorithm. IEEE Trans. Image Processing 3(5), 527–532 (1994)
Hamdi, M., Robert, J.W.: QoS guarantees for shaped bit rate video connections in broadband networks. In: Proc. Int. Conf. Multimedia Networking, Azu- Wakamatsu, Japan (September 1995)
Tsang, D.H.K., Bensaou, B., Lum, S.T.C.: Fuzzy-Based rate Control for Real-Time MPEG Video. IEEE Trans. Fuzzy Systems 6(4) (November 1998)
Mandal, M.K., Idris, F., Panchanathan, S.: A critical evaluation of image and video indexing techniques in the compressed domain. Image and Vision Computing 17, 513–529 (1999)
Yeo, B.L., Liu, B.: Rapid scene analysis on compressed video. IEEE Trans. Circuits and Systems for Video Technology 5, 533–544 (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kim, W., Jang, HJ., Kim, GY. (2006). Transmission Rate Prediction of VBR Motion Image Using the Kalman Filter. In: Gavrilova, M.L., et al. Computational Science and Its Applications - ICCSA 2006. ICCSA 2006. Lecture Notes in Computer Science, vol 3981. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11751588_12
Download citation
DOI: https://doi.org/10.1007/11751588_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34072-0
Online ISBN: 978-3-540-34074-4
eBook Packages: Computer ScienceComputer Science (R0)