Deakin University
Browse

File(s) under permanent embargo

Leveraging Cuboids for Better Motion Modeling in High Efficiency Video Coding

Version 2 2024-06-06, 03:40
Version 1 2022-11-29, 21:37
conference contribution
posted on 2024-06-06, 03:40 authored by A Ahmmed, Manzur MurshedManzur Murshed, M Paul
In conventional video compression systems, motion model is used to approximate the geometry of moving object boundaries. It is possible to relieve motion model from describing discontinuities in the underlying motion field, by incorporating motion hint that can predict the spatial structure of future frames using the structure of reference frames. However, formation of highly accurate motion hint is computationally demanding, in particular for high resolution video sequences. Cuboids, rectangular regions derived using statistical features, attempt to separate out different objects present in the scene; they are computationally efficient and have sparse representation. Leveraging on the advantages of cuboids, in this paper, we propose to discover homogeneous motion regions and their associated motion based on cuboids. Afterwards, the estimated motion models and their domains are applied to form a prediction of the current frame. Experimental results show that a savings in bit rate of 3.96% is achievable over standalone HEVC reference, if this predicted frame is used as an additional reference frame for the current frame.

History

Volume

2020-May

Pagination

2188-2192

Location

Barcelona, Spain

Start date

2020-05-04

End date

2020-05-08

ISSN

1520-6149

eISSN

2379-190X

ISBN-13

9781509066315

Language

eng

Publication classification

E1.1 Full written paper - refereed

Title of proceedings

ICASSP 2020: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing 2020 conference

Event

IEEE International Conference on Acoustics, Speech, and Signal Processing. Conference (2020 : Barcelona, Spain)

Publisher

IEEE

Place of publication

Piscataway, N.J.

Series

International Conference on Acoustics Speech and Signal Processing ICASSP

Usage metrics

    Research Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC