The improvement of intelligent transportation systems requires high-precision vehicle detection under full-weather condition. From the view of unmanned aerial vehicle (UAV), vehicle information in the global scope can be monitored effectively. At present, most of vehicle datasets are monomodal or unregistered multimodal, failing to be trained to detect vehicles under the harsh environment. In this paper, a visible and infrared aerial vehicle dataset, named VIA, has been proposed, which is highly temporal registered and covers a variety of scenarios. In addition, a visible and infrared rotation fusion detection framework based on YOLOv3, named RFN, has been proposed. The framework uses a dual-path feature extraction network to extract features separately and uses rotated bounding boxes to locate vehicles, solving the problem of confusion and redundancy of vehicle information caused by horizontal bounding box detection. Besides, the effectiveness of Oriented Response Network (ORN) and Asymmetric Convolution Blocks (ACB) modules for feature enhancement is explored. The promising results have been obtained in the VIA dataset by this method.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Rotated Fusion Network (RFN) Algorithm for Aerial Vehicle Detection


    Contributors:
    Yang, Feng (author) / Wang, Yumeng (author) / Hu, Haiwei (author)


    Publication date :

    2021-05-28


    Size :

    1360862 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    RVDNet: Rotated Vehicle Detection Network with Mixed Spatial Pyramid Pooling for Accurate Localization

    Zhou, Jianhong / Liang, Zhangzhao / Tan, Zijun et al. | Springer Verlag | 2024


    Rotated quadrotor

    WANG SONG / CHEN WANLI / DUN WENQIANG | European Patent Office | 2015

    Free access

    ROTATED FLOATER

    LEE JONG TAIK / LEE CHUNG CHUL / NOH JEUNG HWAN | European Patent Office | 2020

    Free access

    Rotated section stabilizer

    SAJE ROBERT N / THIEDA STEVEN C | European Patent Office | 2016

    Free access

    Orientation analysis for rotated human face detection

    Zhou, J. / Lu, X. g. / Zhang, D. et al. | British Library Online Contents | 2002