Extracting semantic information of cycling lane based on street view image

Xin Lei; Nina Meng

doi:10.1117/12.3026479

27 March 2024 Extracting semantic information of cycling lane based on street view image

Xin Lei, Nina Meng

Proceedings Volume 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023); 1310510 (2024) https://doi.org/10.1117/12.3026479
Event: 3rd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 2023, Qingdao, China

Abstract

As a sustainable urban transportation mode, cycling has the advantages of energy saving, environmental protection, relieving congestion, and improving road utilization. However, the vast majority of urban road network data are mainly organized and constructed by motor vehicle services, lacking perfect cycling attribute information, which is difficult to meet the needs of cyclists. Therefore, this paper studies a method to extract the semantic information of cycling lanes from street view images. In this method, the detection algorithm yolov7 is used to construct the cycling traffic sign classification model, extracting semantic information related to bicycles from street view images, and then it is matched with the OSM road network data to generate an updated cycling road network. The experimental results show that this method can effectively identify all kinds of cycling traffic signs in the street view images, and the extracted semantic information has a good matching degree with the OSM road network. Using street view images to extract cycling semantic information in roads is an effective means to enrich the cycling attributes of existing road network data.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xin Lei and Nina Meng "Extracting semantic information of cycling lane based on street view image", Proc. SPIE 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 1310510 (27 March 2024); https://doi.org/10.1117/12.3026479

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KEYWORDS

Roads

Semantics

Data modeling

Education and training

Object detection

Detection and tracking algorithms

Panoramic photography

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