Pregled bibliografske jedinice broj: 1184075
A Rethinking of Real-Time Computer Vision-Based Lane Detection
A Rethinking of Real-Time Computer Vision-Based Lane Detection // 2021 IEEE 11th International Conference on Consumer Electronics (ICCE-Berlin)
Berlin, Njemačka, 2021. str. 1-6 doi:10.1109/ICCE-Berlin53567.2021.9720012 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1184075 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
A Rethinking of Real-Time Computer Vision-Based Lane
Detection
Autori
Vajak, Denis ; Vranješ, Mario ; Grbić, Ratko ; Teslić, Nikola
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
2021 IEEE 11th International Conference on Consumer Electronics (ICCE-Berlin)
/ - , 2021, 1-6
Skup
IEEE 11th International Conference on Consumer Electronics
Mjesto i datum
Berlin, Njemačka, 15.11.2021. - 18.11.2021
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
ADAS ; Lane detection ; Computer vision
Sažetak
Lane detection (LD) is one of the most important Advanced Driver Assistance Systems (ADASs) in modern vehicles. In this paper, a new solution for LD based solely on classical computer vision, dubbed HistWind, is presented. A great advantage of the proposed solution is real-time application, and no need for powerful hardware. HistWind is based on a combination of image preprocessing, histogram peak detection, and sliding window line detection and fitting. The parameters are adjusted using particle swarm optimization against an existing training data set and then compared with an existing and freely available deep learning- based solution on a testing set. The results show that HistWind achieves comparable results in terms of precision, recall, and F1 measures, but significantly lower execution time when operating on a CPU. This makes HistWind suitable for real- time implementation on limited hardware resources, which is often installed in modern vehicles. HistWind can process 25 frames per second when processing 1640x590 pixel frames and running on AMD Ryzen 5 1600 CPU with 24 GB of RAM.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo
POVEZANOST RADA
Projekti:
DGS-UNIOS-ZUP 2018-6 - Povećavanje razine pouzdanosti vožnje autonomnih vozila pomoću sustava kamera na vozilu (Vranješ, Mario, DGS - Interni natječaja Sveučilišta Josipa Jurja Strossmayera u Osijeku za znanstvenoistraživačke i umjetničke projekte UNIOS-ZUP 2018) ( CroRIS)
Ustanove:
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek