Robotic perception continues to be one of the main challenges in autonomous robotics. Accurate and real-time perception is very important as it constitutes the basis of important tasks such as decision making and control. The latency of the sensing pipeline is a major limiting factor for the agility of a robot. A novel sensor called an event camera has been recently developed to overcome the limitations of traditional frame-based ones. Event cameras mimic the human perception system as they measure the per-pixel intensity change rather than the actual intensity level. This paper presents our initial investigation of this novel sensing modality by building an event-based dynamic multi-cluster tracker. This can constitute a building-block for higher-level event-based multi-object trackers. The clustering algorithm will be experimentally evaluated in different scenarios including its use for mapping.


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    Titel :

    A Multi-Cluster Tracking Algorithm with an Event Camera


    Beteiligte:


    Erscheinungsdatum :

    01.07.2019


    Format / Umfang :

    1225765 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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