Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/52951
Title: An efficient video coding technique using a novel non-parametric background model
Contributor(s): Chakraborty, Subrata  (author)orcid ; Paul, Manoranjan (author); Murshed, Manzur (author); Ali, Mortuza (author)
Publication Date: 2014-09-08
DOI: 10.1109/ICMEW.2014.6890590
Handle Link: https://hdl.handle.net/1959.11/52951
Abstract: 

Video coding technique with a background frame, extracted from mixture of Gaussian (MoG) based background modeling, provides better rate distortion performance by exploiting coding efficiency in uncovered background areas compared to the latest video coding standard. However, it suffers from high computation time, low coding efficiency for dynamic videos, and prior knowledge requirement of video content. In this paper, we present a novel adaptive weighted non-parametric (WNP) background modeling technique and successfully embed it into HEVC video coding standard. Being non-parametric (NP), the proposed technique naturally exhibits superior performance in dynamic background scenarios compared to MoG-based technique without a priori knowledge of video data distribution. In addition, the WNP technique significantly reduces noise-related drawbacks of existing NP techniques to provide better quality video coding with much lower computation time as demonstrated through extensive comparative studies against NP, MoG and HEVC techniques.

Publication Type: Conference Publication
Conference Details: ICMEW 2014: IEEE International Conference on Multimedia and Expo Workshops, Chengdu, China, 14th - 18th July, 2014
Source of Publication: 2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), p. 1-6
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Place of Publication: Los Alamitos, United States of America
Fields of Research (FoR) 2020: 460199 Applied computing not elsewhere classified
460305 Image and video coding
461199 Machine learning not elsewhere classified
Socio-Economic Objective (SEO) 2020: 280115 Expanding knowledge in the information and computing sciences
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Series Name: Proceedings (IEEE International Conference on Multimedia and Expo)
Appears in Collections:Conference Publication
School of Science and Technology

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