Recently, automated emergency brake systems for pedestrian have been commercialized. However, they cannot detect crossing pedestrians when turning at intersections because the field of view is not wide enough. Thus, we propose to utilize a surround view camera system becoming popular by making it into stereo vision which is robust for the pedestrian recognition. However, conventional stereo camera technologies cannot be applied due to fisheye cameras and uncalibrated camera poses. Thus we have created the new method to absorb difference of the pedestrian appearance between cameras by machine learning for the stereo vision. The method of stereo matching between image patches in each camera image was designed by combining D-Brief and NCC with SVM. Good generalization performance was achieved by it compared with individual conventional algorithms. Furthermore, feature amounts of the point cloud reconstructed by the stereo pairs are utilized with Random Forest to discriminate pedestrians. The algorithm was evaluated for the actual camera images of crossing pedestrians at various intersections, and 96.0% of pedestrian tracking rate with high position detection accuracy was achieved. They were compared with Faster R-CNN as the best pattern recognition technique, and our proposed method indicated better detection performance.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Machine Learning-based Stereo Vision Algorithm for Surround View Fisheye Cameras


    Beteiligte:


    Erscheinungsdatum :

    01.11.2018


    Format / Umfang :

    952482 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    An Online Learning System for Wireless Charging Alignment using Surround-view Fisheye Cameras

    Dahal, Ashok / Kumar, Varun Ravi / Yogamani, Senthil et al. | ArXiv | 2021

    Freier Zugriff

    An Online Learning System for Wireless Charging Alignment Using Surround-View Fisheye Cameras

    Dahal, Ashok / Kumar, Varun Ravi / Yogamani, Senthil et al. | IEEE | 2022


    SVDistNet: Self-Supervised Near-Field Distance Estimation on Surround View Fisheye Cameras

    Ravi Kumar, Varun / Klingner, Marvin / Yogamani, Senthil et al. | IEEE | 2022


    Near-Field Perception for Low-Speed Vehicle Automation Using Surround-View Fisheye Cameras

    Eising, Ciaran / Horgan, Jonathan / Yogamani, Senthil | IEEE | 2022


    Multi-task near-field perception for autonomous driving using surround-view fisheye cameras

    Ravi Kumar, Varun / Technische Universität Ilmenau | TIBKAT | 2021

    Freier Zugriff