This paper proposes a semantic mapping method based on pedestrian activity in the urban road environment. Pedestrian activity patterns are learned from pedestrian tracks collected by a mobile platform. With the learned knowledge of pedestrian activity, semantic mapping is performed using Bayesian classification techniques. The proposed method is tested in real experiments, and shows promising results in recognizing four activity-related semantic properties of the urban road environment: pedestrian path, entrance/exit, pedestrian crossing and sidewalk.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Learning pedestrian activities for semantic mapping


    Contributors:
    Qin, B. (author) / Chong, Z. J. (author) / Bandyopadhyay, T. (author) / Ang, M. H. (author) / Frazzoli, E. (author) / Rus, D. (author)


    Publication date :

    2014-05-01


    Size :

    2089910 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Pedestrian activities: Enhancing knowledge and visibility of walking and place activities

    Koszowski, Caroline / Technische Universität Dresden | SLUB | 2025



    Pedestrian activities: enhancing knowledge and visibility of walking and place activities

    Koszowski, Caroline / Technische Universität Dresden | SLUB | 2025


    Mapping patterns of pedestrian fatal accidents in Israel

    Prato, Carlo Giacomo | Online Contents | 2012


    Guidelines for Bicycle and Pedestrian Facilities: First-Year Activities

    D. S. Hauser / R. J. Benz / H. G. Hawkins | NTIS | 1995