This manuscript conducts a comparison on modern object detection systems in their ability to detect multiple maritime vessel classes. Three highly scoring algorithms from the Pascal VOC Challenge, Histogram of Oriented Gradients by Dalal and Triggs, Exemplar-SVM by Malisiewicz, and Latent-SVM with Deformable Part Models by Felzenszwalb, were compared to determine performance of recognition within a specific category rather than the general classes from the original challenge. In all cases, the histogram of oriented edges was used as the feature set and support vector machines were used for classification. A summary and comparison of the learning algorithms is presented and a new image corpus of maritime vessels was collected. Precision-recall results show improved recognition performance is achieved when accounting for vessel pose. In particular, the deformable part model has the best performance when considering the various components of a maritime vessel.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen


    Exportieren, teilen und zitieren



    Titel :

    Comparison of Object Detection Algorithms on Maritime Vessels


    Beteiligte:
    M. Chua (Autor:in) / D. W. Aha (Autor:in) / B. Auslander (Autor:in) / K. Gupta (Autor:in) / B. Morris (Autor:in)

    Erscheinungsdatum :

    2014


    Format / Umfang :

    12 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch




    Maritime Autonomous Vessels

    Xu, Haitong ;Moreira, Lúcia ;Guedes Soares, Carlos | TIBKAT | 2023

    Freier Zugriff

    Maritime Autonomous Vessels

    Xu, Haitong ;Moreira, Lúcia ;Guedes Soares, Carlos | GWLB - Gottfried Wilhelm Leibniz Bibliothek | 2023

    Freier Zugriff

    New maritime cargo vessels

    Engineering Index Backfile | 1953


    SENSOR SYSTEM FOR MARITIME VESSELS

    SURESH THIRU VIKRAM / ZHITELZEYF ALEXANDER / KHAKHARIA MOHIT ARVIND et al. | Europäisches Patentamt | 2021

    Freier Zugriff

    SENSOR SYSTEM FOR MARITIME VESSELS

    SURESH THIRU VIKRAM / ZHITELZEYF ALEXANDER / KHAKHARIA MOHIT ARVIND et al. | Europäisches Patentamt | 2020

    Freier Zugriff