The need for safety on roads has made the development of autonomous driving one of the most important topics for Computer Vision research. This thesis focuses on the lane detection problem using images obtained with lateral fisheye cameras, firstly by studying the state-of-the-art and the spherical model, then by developing two methods to solve this task. While the first is based on traditional Computer Vision, the second makes use of a Convolutional Neural Network. Results are then compared.
Lane Detection System for Intelligent Vehicles using Lateral Fisheye Cameras
Valente, Alex
2020/2021
Abstract
The need for safety on roads has made the development of autonomous driving one of the most important topics for Computer Vision research. This thesis focuses on the lane detection problem using images obtained with lateral fisheye cameras, firstly by studying the state-of-the-art and the spherical model, then by developing two methods to solve this task. While the first is based on traditional Computer Vision, the second makes use of a Convolutional Neural Network. Results are then compared.File in questo prodotto:
File | Dimensione | Formato | |
---|---|---|---|
alex_valente_tesi.pdf
accesso aperto
Dimensione
4.01 MB
Formato
Adobe PDF
|
4.01 MB | Adobe PDF | Visualizza/Apri |
The text of this website © Università degli studi di Padova. Full Text are published under a non-exclusive license. Metadata are under a CC0 License
Utilizza questo identificativo per citare o creare un link a questo documento:
https://hdl.handle.net/20.500.12608/22886