In this paper, we focus on fine-grained recognition of vehicles mainly in traffic surveillance applications. We propose an approach that is orthogonal to recent advancements in fine-grained recognition (automatic part discovery and bilinear pooling). In addition, in contrast to other methods focused on fine-grained recognition of vehicles, we do not limit ourselves to a frontal/rear viewpoint, but allow the vehicles to be seen from any viewpoint. Our approach is based on 3-D bounding boxes built around the vehicles. The bounding box can be automatically constructed from traffic surveillance data. For scenarios where it is not possible to use precise construction, we propose a method for an estimation of the 3-D bounding box. The 3-D bounding box is used to normalize the image viewpoint by “unpacking” the image into a plane. We also propose to randomly alter the color of the image and add a rectangle with random noise to a random position in the image during the training of convolutional neural networks (CNNs). We have collected a large fine-grained vehicle data set BoxCars116k, with 116k images of vehicles from various viewpoints taken by numerous surveillance cameras. We performed a number of experiments, which show that our proposed method significantly improves CNN classification accuracy (the accuracy is increased by up to 12% points and the error is reduced by up to 50% compared with CNNs without the proposed modifications). We also show that our method outperforms the state-of-the-art methods for fine-grained recognition.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    BoxCars: Improving Fine-Grained Recognition of Vehicles Using 3-D Bounding Boxes in Traffic Surveillance


    Beteiligte:
    Sochor, Jakub (Autor:in) / Spanhel, Jakub (Autor:in) / Herout, Adam (Autor:in)


    Erscheinungsdatum :

    01.01.2019


    Format / Umfang :

    2708057 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    DOOR ASSEMBLIES FOR INSULATED BOXCARS AND REFRIGERATED BOXCARS

    ABERLE DAN | Europäisches Patentamt | 2023

    Freier Zugriff


    Train of Frozen Boxcars Model for Fluidic Harvesters

    Danesh-Yazdi, Amir / Goushcha, Oleg / Elvin, Niell et al. | AIAA | 2017


    Research on Vehicle Recognition Based on Unpacking 3D Bounding Boxes of Monocular Camera in Traffic Scene

    Wang, Wei / Tang, Xinyao / Tian, Shangwei et al. | British Library Conference Proceedings | 2020


    Research on Vehicle Recognition Based on Unpacking 3D Bounding Boxes of Monocular Camera in Traffic Scene

    Zhang, Chaoyang / Cui, Hua / Tian, Shangwei et al. | SAE Technical Papers | 2020