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A two-stage h.264 based video compression method for automotive cameras

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Wang, Yiting, Chan, Pak Hung and Donzella, Valentina (2022) A two-stage h.264 based video compression method for automotive cameras. In: The 5th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS) 2022, Coventry, UK, 24-26 May 2022. Published in: Proccedings of the The 5th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS) 2022 ISBN 9781665497701. doi:10.1109/ICPS51978.2022.9816916

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Official URL: https://doi.org/10.1109/ICPS51978.2022.9816916

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Abstract

With the development of automated vehicles and advanced driver assistance systems, the compression of the large amount of data generated by the vehicle camera sensors becomes a necessary processing step to improve the automated driving system efficiency. H.264 is a widely adopted video compression scheme, and it has been designed for human vision. Rate control in H.264 uses fixed quantisation parameter, however, this process can lead to fluctuation in different regions of the image quality of each frame. In this paper, we propose a two-stageH.264 based video compression framework, named “Two Stage Compression (TSC)”, to compress the automotive camera videos with different values of compression rate in different regions of each frame. In the first stage, each frame will be divided into the region-of-interest and the region-out-of-interest. In the second- stage, different compression ratios will be applied based on the importance of the region. The experimental results show that under the same overall compression ratio, our proposed TSC increments the semantic-aware PSNR by 3.213 dB compared to uniform H.264 compression. Our method is also compared to uniform H.264 compression using a segmentation algorithm, with an improvement of 1.77% in mIOU, the average Intersection over- Union

Item Type: Conference Item (Paper)
Subjects: Q Science > Q Science (General)
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TL Motor vehicles. Aeronautics. Astronautics
Divisions: Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group)
Library of Congress Subject Headings (LCSH): Automated vehicles , Driver assistance systems , Image processing, Video compression , Machine learning , Intelligent transportation systems, Automobiles -- Automatic control
Journal or Publication Title: Proccedings of the The 5th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS) 2022
Publisher: IEEE
ISBN: 9781665497701
Official Date: 18 July 2022
Dates:
DateEvent
18 July 2022Published
10 April 2022Accepted
DOI: 10.1109/ICPS51978.2022.9816916
Status: Peer Reviewed
Publication Status: Published
Reuse Statement (publisher, data, author rights): © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 21 June 2022
Date of first compliant Open Access: 23 June 2022
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
Industrial Fellowships schemeRoyal Academy of Engineeringhttp://dx.doi.org/10.13039/501100000287
HVM CATAPULTInnovate UKhttp://dx.doi.org/10.13039/501100006041
Conference Paper Type: Paper
Title of Event: The 5th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS) 2022
Type of Event: Conference
Location of Event: Coventry, UK
Date(s) of Event: 24-26 May 2022
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