Many approaches to moving object detection for traffic monitoring and video surveillance proposed in the literature are based on background suppression methods. How to correctly and efficiently update the background model and how to deal with shadows are two of the more distinguishing and challenging features of such approaches. This work presents a general-purpose method for segmentation of moving visual objects (MVO) based on an object-level classification in MVO, ghosts and shadows. Background suppression needs the background model to be estimated and updated: we use motion and shadow information to selectively exclude from the background model MVO and their shadows, while retaining ghosts. The color information (in the HSV color space) is exploited to shadow suppression and, consequently, to enhance both MVO segmentation and background update.


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    Titel :

    Detecting objects, shadows and ghosts in video streams by exploiting color and motion information


    Beteiligte:
    Cucchiara, R. (Autor:in) / Grana, C. (Autor:in) / Piccardi, M. (Autor:in) / Prati, A. (Autor:in)


    Erscheinungsdatum :

    2001-01-01


    Format / Umfang :

    652501 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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    Cucchiara, R. / Grana, C. / Piccardi, M. et al. | British Library Conference Proceedings | 2001


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    Duque, D. / Santos, H. / Cortez, P. | IEEE | 2005


    Moving Object Detection Unaffected by Cast Shadows, Highlights and Ghosts

    Duque, D. / Santos, H. / Cortez, P. | British Library Conference Proceedings | 2005


    Analysis and Detection of Shadows in Video Streams: A Comparative Evaluation

    Prati, A. / Cucchiara, R. / Mikic, I. et al. | British Library Conference Proceedings | 2001


    Analysis and detection of shadows in video streams: a comparative evaluation

    Prati, A. / Cucchiara, R. / Mikic, I. et al. | IEEE | 2001