We must always measure a distance from the own vehicle to the front one to prevent the collision accident. In this paper the authors desribed a new technique for measuring the distance using stereoscopic images. A vehicle can be recognized as a set of object points that are same distance from the stereo cameras. So, disparity map is projected in the depth direction. This map is called 'Projection Disparity Map'. In the projection disparity map the disparities of the vehicle are translated into the straight line. So one can detect the front vehicle by extracting the straight line. For verifying this method, the authors applied it to the stereosocpic images that are acquired on the expressway. And the efficieny was shown by experiments.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Extraction of the front vehicle using projection disparity map


    Weitere Titelangaben:

    Bestimmung des Abstandes zum vorausfahrenden Fahrzeug aus stereoskopischen Bildern


    Beteiligte:
    Tsunashima, N. (Autor:in) / Nakajima, M.T. (Autor:in)


    Erscheinungsdatum :

    1998


    Format / Umfang :

    4 Seiten, 4 Bilder, 3 Quellen



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




    Extraction of the Front Vehicle Using Projection Disparity Map

    Tsunashima, N. / Nakajima, M. / Society of Automotive Engineers of Japan | British Library Conference Proceedings | 1998


    Fast Vehicle Detection Using a Disparity Projection Method

    Chen, Jing / Xu, Wenqiang / Xu, Haitao et al. | IEEE | 2018


    An Obstacle Extraction Method Using Virtual Disparity Image

    Suganuma, N. / Fujiwara, N. / Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2007


    An Obstacle Extraction Method Using Virtual Disparity Image

    Suganuma, N. / Fujiwara, N. | IEEE | 2007


    Vehicle Detection and Disparity Estimation Using Blended Stereo Images

    Zhou, Changxin / Liu, Yazhou / Sun, Quansen et al. | IEEE | 2021