Research on the Lane Recognition Method Based on Computer Vision

Weiqi Kong

doi:10.54254/2755-2721/1/2023009

Research Article

Open access

Published on 31 May 2023

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Kong,W. (2023). Research on the Lane Recognition Method Based on Computer Vision. Applied and Computational Engineering,1,52-62.

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Research on the Lane Recognition Method Based on Computer Vision

Weiqi Kong *^,1,

¹ Jiangxi Normal University (Yaohu Campus)

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/1/2023009

Abstract

The lane line is the most important traffic sign in road traffic and plays a significant function in restricting and guaranteeing the running of vehicles. Whether in the vehicle safety driving system or in the intelligent vehicle navigation based on machine vision, lane detection and recognition is a basic and necessary function module. This can enable future in-depth studies on intelligent transportation while also lowering the likelihood of traffic accidents.

Keywords

lane recognition, image semantic segmentation network, geometric detection, anchor representation, image segmentation

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References

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[2]. Pingping Lu, Chen Cui, Shaobing Xu, Huei Peng, Fan Wang SUPER: A New Lane Detection System [J] Computer Vision and Pattern Recognition 2020, Issue 3, Volume 2, P20-21

[3]. Ruijin Liu, Zejian Yuan, Tie Liu, Zhiliang Xiong End to End Lane Shape Prediction with Transformers [J] Computer Vision and Pattern Recognition

[4]. Zequn Qin, Huanyu Wang, Xi Li Ultra Fast Structure aware Deep Lane Detection [J] Computer Vision and Pattern Recognition Volume 3, Volume 2, 2020, P7-9

[5]. DongWu, ManwenLiao, Weitian Zhang, XinggangWang, Xiang Bai, Wenqing Cheng, Wenyu Liu YOLOP: You Only Look Once for Panoptic Driving Perception [J] Computer Vision and Pattern Recognition Volume 2, Issue 1, 2020, P25-27

[6]. Ruochen Yin, Biao Yu, Huapeng Wu, Yutao Song, Runxin Niu Fusion Lane: Multi_Sensor Fusion for Lane Marking Semantic Segmentation Using Deep Neural Networks[J] Computer Vision and Pattern Recognition Volume 3, Issue 3, 2020, P10-P12

[7]. Hang Xu, Shaoju Wang, Xinyue Cai, Wei Zhang, Xiaodan Liang, Zhenguo Li Curve Lane NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending[J]Computer Vision and Pattern Recognition Volume 2, Issue 2, 2020, P9-11

[8]. Netalee Efrat, Max Bluvstein, Noa Garnett, Dan Levi, Shaul Oron, Bat El Shlomo Gen-Lane Net. A Generalized and Scalable Approach for 3D Lane Detection [J] Computer Vision and Pattern Recognition Volume 1, Issue 1, 2019, P15-P17

Cite this article

Kong,W. (2023). Research on the Lane Recognition Method Based on Computer Vision. Applied and Computational Engineering,1,52-62.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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Conference date: 1 January 0001

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Series: Applied and Computational Engineering

Volume number: Vol.1

ISSN：2755-2721(Print) / 2755-273X(Online)

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