Pedestrian protection systems are being included by many automobile manufacturers in their commercial vehicles. However, improving the accuracy of these systems is imperative since the difference between an effective and a non-effective intervention can depend only on a few centimeters or on a fraction of a second. In this paper, we describe a method to carry out the prediction of pedestrian locations and pose and to classify intentions up to 1 s ahead in time applying Balanced Gaussian Process Dynamical Models (B-GPDM) and naïve-Bayes classifiers. These classifiers are combined in order to increase the action classification precision. The system provides accurate path predictions with mean errors of 24.4 cm, for walking trajectories, 26.67 cm, for stopping trajectories and 37.36 cm for starting trajectories, at a time horizon of 1 second.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Pedestrian Intention and Pose Prediction through Dynamical Models and Behaviour Classification


    Beteiligte:
    Quintero, R. (Autor:in) / Parra, I. (Autor:in) / Llorca, D. F. (Autor:in) / Sotelo, M. A. (Autor:in)


    Erscheinungsdatum :

    2015-09-01


    Format / Umfang :

    756292 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Pedestrian Path, Pose, and Intention Prediction Through Gaussian Process Dynamical Models and Pedestrian Activity Recognition

    Quintero Minguez, Raul / Parra Alonso, Ignacio / Fernandez-Llorca, David et al. | IEEE | 2019


    Pedestrian Crossing Intention Prediction at Red-Light Using Pose Estimation

    Zhang, Shile / Abdel-Aty, Mohamed / Wu, Yina et al. | IEEE | 2022


    Learning to Forecast Pedestrian Intention from Pose Dynamics

    Ghori, Omair / Mackowiak, Radek / Bautista, Miguel et al. | IEEE | 2018


    Joint Pedestrian Motion State and Device Pose Classification

    Kasebzadeh, Parinaz / Radnosrati, Kamiar / Hendeby, Gustaf et al. | BASE | 2020

    Freier Zugriff

    Early Warning Pedestrian Crossing Intention From Its Head Gesture using Head Pose Estimation

    Perdana, Muhammad Ilham / Anggraeni, Wiwik / Sidharta, Hanugra Aulia et al. | IEEE | 2021