We present a probabilistic framework for the joint estimation of pedestrian head and body orientation from a mobile stereo vision platform. For both head and body parts, we convert the responses of a set of orientation-specific detectors into a (continuous) probability density function. The parts are localized by means of a pictorial structure approach, which balances part-based detector responses with spatial constraints. Head and body orientations are estimated jointly to account for anatomical constraints. The joint single-frame orientation estimates are integrated over time by particle filtering. The experiments involved data from a vehicle-mounted stereo vision camera in a realistic traffic setting; 65 pedestrian tracks were supplied by a state-of-the-art pedestrian tracker. We show that the proposed joint probabilistic orientation estimation framework reduces the mean absolute head and body orientation error up to 15° compared with simpler methods. This results in a mean absolute head/body orientation error of about 21°/19°, which remains fairly constant up to a distance of 25 m. Our system currently runs in near real time (8–9 Hz).


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A Probabilistic Framework for Joint Pedestrian Head and Body Orientation Estimation


    Beteiligte:


    Erscheinungsdatum :

    2015-08-01


    Format / Umfang :

    2110865 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    JOINT PROBABILISTIC PEDESTRIAN HEAD AND BODY ORIENTATION ESTIMATION

    Flohr, F. / Dumitru-Guzu, M. / Kooij, J. et al. | British Library Conference Proceedings | 2014



    A Novel Pedestrian Orientation Estimation Method

    Gao, Ming / Jin, LiSheng / Jiang, Yuying et al. | TIBKAT | 2020


    JOINT PROBABILISTIC DATA ASSOCIATION FUSION APPROACH FOR PEDESTRIAN DETECTION

    Garcia, F. / Escalera, A. / Armingol, J. et al. | British Library Conference Proceedings | 2013