This paper proposes a novel method for vehicle detection and tracking using a vehicle-mounted monocular camera in an intelligent vehicle system. Speed-based Adaptive Perception Zone (APZ) is first defined to ensure that the vehicle minimizes the spatial extent of the region it perceives according to its own speed. Vehicle candidates are generated using brake lights detection through color segmentation method and verified by a rule-based clustering approach. A tracking-by-detection scheme based on Harris-SIFT feature matching is then used to learn the template of the detected vehicle on line, localize and track the corresponding vehicle in live video. Our system was validated in real conditions in our prototype vehicle with state-of-the-art performance, equivalent and sometimes surpassing other methods recently published.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    On-Road Vehicle Detection Based on Color Segmentation and Tracking Using Harris-SIFT



    Erschienen in:

    Advanced Materials Research ; 433-440 ; 5334-5338


    Erscheinungsdatum :

    2012-01-03


    Format / Umfang :

    5 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





    A SIFT-BASED MEAN SHIFT ALGORITHM FOR MOVING VEHICLE TRACKING

    Liang, W. / Xie, X. / Wang, J. et al. | British Library Conference Proceedings | 2014


    Color Road Segmentation And Video Obstacle Detection

    Turk, Matthew A. / Marra, Martin | SPIE | 1987


    Hungarian-Particle Filtering Based Segmentation for On-Road Visual Vehicle Detection and Tracking

    Aminuddin, Nuramin Fitri / Tukiran, Zarina / Joret, Ariffuddin et al. | IEEE | 2022


    Object tracking using SIFT features and mean shift

    Zhou, H. / Yuan, Y. / Shi, C. | British Library Online Contents | 2009