This paper presents a new approach to generate hypotheses about the presence of pedestrians in an infrared image. Information about maximally stable extremal regions is used to locate the warmest regions on the image, which are considered to be potential human heads. To capture the complete human body, these regions are scaled based on the range data of a lidar sensor. Closely related regions are merged into one bigger region to avoid the segmentation which arises from the heterogeneous heating emission of a dressed human. Additionally, the area and perimeter of each potential pedestrian are examined to discard artificial objects. The optimal decision measure is sought so that all pedestrians are extracted from a scene. All remaining hypotheses should be further processed with a statistical classifier.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Pedestrian detection based on maximally stable extremal regions


    Contributors:


    Publication date :

    2010-06-01


    Size :

    790189 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Pedestrian Detection Based on Maximally Stable Extremal Regions, pp. 910-914

    Frolov, V. / Puente Leon, F. / Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2010


    MULTI-SENSOR SELF-LOCALIZATION BASED ON MAXIMALLY STABLE EXTREMAL REGIONS

    Deusch, H. / Wiest, J. / Reuter, S. et al. | British Library Conference Proceedings | 2014


    Robust wide-baseline stereo from maximally stable extremal regions

    Matas, J. / Chum, O. / Urban, M. et al. | British Library Online Contents | 2004



    Maximally Stable Control and reconstruction

    Vaněček, A. | TIBKAT | 1984