Integrated Compressed Sensing and YOLOv4 for Application in Image-storage and Object-recognition of Dashboard Camera

Jim Wei Wu, Cheng Chia Wu, Wen Shan Cen, Shao An Chao, Jui Tse Weng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper focuses on the research of the dashboard camera for improving the storage space and object recognition. The experiments showed that the CS method of ISTA-Net (Iterative Shrinkage Thresholding Algorithm with Network) can reduce the storage space by at least 60% and without obviously sacrificing the image quality. Furthermore, the recognition method by YOLOv4 can overcome the variety of environments, which can reach the recognition ratio of over 80% in a small 480x480 pixels. The recognition function can help to quickly catch the key features (ex: car, traffic signal, pedestrian, etc.) in the storage data of the dashboard camera.

Original languageEnglish
Title of host publication2021 Australian and New Zealand Control Conference, ANZCC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7-11
Number of pages5
ISBN (Electronic)9781665416504
DOIs
StatePublished - 2021
Event2021 Australian and New Zealand Control Conference, ANZCC 2021 - Gold Coast, Australia
Duration: 25 Nov 202126 Nov 2021

Publication series

Name2021 Australian and New Zealand Control Conference, ANZCC 2021

Conference

Conference2021 Australian and New Zealand Control Conference, ANZCC 2021
Country/TerritoryAustralia
CityGold Coast
Period25/11/2126/11/21

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