Variable-Bit-Rate Video Frame-Size Prediction by the Extended Kalman Filter Using Levenberg-Marquardt Algorithm

It is crucial to dynamically predict the future frame-sizes (bit-rates) for multimedia networking. All of the conventional bit-rate predictors are based on the assumption that instantaneous bit-rates are known precisely all the time (in the absence of uncertainty) which is surely not realistic in pr...

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Bibliographic Details
Published in:IEEE transactions on broadcasting Vol. 69; no. 1; pp. 75 - 84
Main Authors: Chang, Shih Yu, Wu, Hsiao-Chun, Yan, Kun
Format: Journal Article
Language:English
Published: New York IEEE 01.03.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Covariance matrices
expectation–maximization (EM) algorithm
Extended Kalman filter
Extended Kalman filter (EKF)
Heuristic algorithms
Kalman filters
Levenberg–Marquardt algorithm (LMA)
MPEG-4
Multimedia
multimedia network
Optimization
Prediction algorithms
Robustness (mathematics)
Signal to noise ratio
Streaming media
Transform coding
Uncertainty
variable-bit-rate (VBR) video streaming
Video compression
ISSN:0018-9316, 1557-9611
Online Access:Get full text
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Summary:It is crucial to dynamically predict the future frame-sizes (bit-rates) for multimedia networking. All of the conventional bit-rate predictors are based on the assumption that instantaneous bit-rates are known precisely all the time (in the absence of uncertainty) which is surely not realistic in practice. In this work, we propose a new expectation-maximization (EM) based extended Kalman filter (EKF) to predict the bit-rates, where the EKF state-transition models will be optimized by the Levenberg-Marquardt algorithm (LMA). The main advantages of our proposed novel EKF-based bit-rate prediction approach are given as follows. First, our proposed EKF-based predictor can optimally estimate the bit-rates in the presence of uncertainty and/or noise. Second, our proposed novel EKF-based bit-rate prediction approach does not require a separate classifier to determine the individual frame-types as the conventional approach so our approach would be more robust than the conventional approach. Numerical evaluation of bit-rate (frame-size) prediction is also conducted over three movies encoded by the MPEG-4 standard. Compared to the existing Kalman-filter based bit-rate prediction methods, our proposed new LMA-EKF predictor can achieve much better performance in terms of the normalized mean square error (NMSE) and the inverse of signal-to-noise-ratio (SNR).
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ISSN:0018-9316
1557-9611
DOI:10.1109/TBC.2022.3185461