Video coding with dynamic background
Author
Paul, Manoranjan
Lin, Weisi
Lau, Chiew Tong
Lee, Bu-Sung
Date of Issue
2013School
School of Computer Engineering
Version
Published version
Abstract
Motion estimation (ME) and motion compensation (MC) using variable block size, sub-pixel search, and multiple reference frames (MRFs) are the major reasons for improved coding performance of the H.264 video coding standard over other contemporary coding standards. The concept of MRFs is suitable for repetitive motion, uncovered background, non-integer pixel displacement, lighting change, etc. The requirement of index codes of the reference frames, computational time in ME & MC, and memory buffer for coded frames limits the number of reference frames used in practical applications. In typical video sequences, the previous frame is used as a reference frame with 68–92% of cases. In this article, we propose a new video coding method using a reference frame [i.e., the most common frame in scene (McFIS)] generated by dynamic background modeling. McFIS is more effective in terms of rate-distortion and computational time performance compared to the MRFs techniques. It has also inherent capability of scene change detection (SCD) for adaptive group of picture (GOP) size determination. As a result, we integrate SCD (for GOP determination) with reference frame generation. The experimental results show that the proposed coding scheme outperforms the H.264 video coding with five reference frames and the two relevant state-of-the-art algorithms by 0.5–2.0 dB with less computational time.
Subject
DRNTU::Engineering::Computer science and engineering
Type
Journal Article
Series/Journal Title
EURASIP journal on advances in signal processing
Rights
© 2013 Paul et al; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This paper was published in EURASIP Journal on Advances in Signal Processing and is made available as an electronic reprint (preprint) with permission of The Author(s). The paper can be found at the following official DOI: [http://dx.doi.org/10.1186/1687-6180-2013-11]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
Collections
http://dx.doi.org/10.1186/1687-6180-2013-11
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