This paper presents an algorithm for ego-positioning by using a low-cost monocular camera for systems based on the Internet-of-Vehicles. To reduce the computational and memory requirements, as well as the communication load, we tackle the model compression task as a weighted $k$-cover problem for better preserving the critical structures. For real-world vision-based positioning applications, we consider the issue of large scene changes and introduce a model update algorithm to address this problem. A large positioning data set containing data collected for more than a month, 106 sessions, and 14 275 images is constructed. Extensive experimental results show that submeter accuracy can be achieved by the proposed ego-positioning algorithm, which outperforms existing vision-based approaches.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Vision-Based Positioning for Internet-of-Vehicles


    Beteiligte:
    Chen, Kuan-Wen (Autor:in) / Wang, Chun-Hsin (Autor:in) / Wei, Xiao (Autor:in) / Liang, Qiao (Autor:in) / Chen, Chu-Song (Autor:in) / Yang, Ming-Hsuan (Autor:in) / Hung, Yi-Ping (Autor:in)


    Erscheinungsdatum :

    01.02.2017


    Format / Umfang :

    3476657 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Vision-Based Positioning for Internet-of-Vehicles

    Chen, Kuan-Wen | Online Contents | 2017


    Internet of Vehicles Communication Method and Positioning Method, and Internet of Vehicles Communications Apparatus

    ZHANG YUXIANG / XIE HONG / ZHOU KAI | Europäisches Patentamt | 2021

    Freier Zugriff

    Vehicle positioning method and system of Internet of Vehicles

    ZENG JIJUN / LONG ZHENYUE / ZHANG XIAOLU et al. | Europäisches Patentamt | 2022

    Freier Zugriff

    Vision-Based Indoor Positioning System for Connected Vehicles in Small-scale Testbed Environments

    Hamza, Mahmoud S. / Shehata, Omar M. / Morgan, Elsayed I. et al. | IEEE | 2024