This paper introduces a feature detection method developed through machine learning specifically tailored for event-camera based visual odometry techniques used in reconstructing trajectories for unmanned aerial vehicles. The proposed approach leverages machine-learned features to improve the precision of trajectory reconstruction. Unlike conventional visual odometry methods, which often struggle in low light and high-speed scenarios, the event-camera-based method addresses these challenges by focusing solely on detecting and processing changes in the visual scene. The machine-learned features are designed to capture the distinctive attributes of event-camera data, thereby refining the accuracy of trajectory reconstruction. The inference pipeline consists of a module that is iterated twice sequentially, comprising a Squeeze-and-Excite block and a ConvLSTM block with residual connection. This is succeeded by a final convolutional layer that generates trajectory information for corners in the form of heatmap sequences. In the experimental phase, a series of images was gathered using an event-camera in outdoor settings for both training and testing purposes.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Improving Keypoints Tracking With Machine-Learned Features in Event-Camera-Based Visual Odometry


    Beteiligte:


    Erscheinungsdatum :

    03.06.2024


    Format / Umfang :

    2737482 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Trajectory reconstruction by means of an event-camera-based visual odometry method and machine learned features

    Chiodini, S. / Trevisanuto, G. / Bettanini, C. et al. | TIBKAT | 2023

    Freier Zugriff

    SPiKeS: Superpixel-Keypoints structure for robust visual tracking

    Derue, F. o. / Bilodeau, G. A. / Bergevin, R. | British Library Online Contents | 2018


    Feature Tracking For Visual Odometry

    HUNT SHAWN | Europäisches Patentamt | 2019

    Freier Zugriff

    Feature tracking for visual odometry

    HUNT SHAWN | Europäisches Patentamt | 2020

    Freier Zugriff

    Learning good features for visual odometry

    TRAN QUOC-HUY / CHANDRAKER MANMOHAN / KIM HYO JIN | Europäisches Patentamt | 2020

    Freier Zugriff