A vision based rear obstacle detection system is one of the most essential technologies, which can be used in many applications such as a parking assistance systems and intelligent vehicles. Stereo matching based obstacle detection methods have two inherent limitations, including sensitivity to illumination variation and high computational complexity. To overcome these problems, we present a hierarchical census transform (HCT)-based stereo matching method, and proposes a real-time rear obstacle detection system using fisheye stereo cameras. It includes two major components: firstly, we use a hierarchical approach to improve computational efficiency and reduce dependency on a matching window size. Computation time can also be accelerated with compute unified device architecture (CUDA) implementation because we designed the proposed method for parallel processing. Secondly, our method provides more accurate depth information, especially for moving objects, through cost aggregation using color and motion information. Experimental results show satisfactory performance under various real parking environments. The performance of the proposed method is superior to those of the conventional methods in terms of runtime and accuracy of depth estimation. Moreover, correct detection rate of the proposed system is 12.51% better than those of other systems, while its false and miss detection rates are 11.09% and 12.51% lower than those of other detection systems.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Rear obstacle detection system with fisheye stereo camera using HCT


    Beteiligte:
    Kim, Deukhyeon (Autor:in) / Choi, Jinwook (Autor:in) / Yoo, Hunjae (Autor:in) / Yang, Ukil (Autor:in) / Sohn, Kwanghoon (Autor:in)

    Erschienen in:

    Expert Systems with Applications ; 42 , 17-18 ; 6295-6305


    Erscheinungsdatum :

    2015


    Format / Umfang :

    11 Seiten, 28 Quellen




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch




    Object detection and classification using a rear in-vehicle fisheye camera

    Tadjine,H.H. / Hess,M. / Karsten,S. et al. | Kraftfahrwesen | 2012


    Object Detection and Classification Using a Rear In-Vehicle Fisheye Camera

    Tadjine, HadjHamma / Hess, Markus / Karsten, Schulze | Springer Verlag | 2012


    Object Detection and Classification Using a Rear In-Vehicle Fisheye Camera

    Tadjine, HadjHamma / Hess, Markus / Karsten, Schulze | Tema Archiv | 2012


    Wide rear vehicle recognition using a fisheye lens camera image

    Jeong, Jin-Seong / Kim, Hyun-Tae / Kim, Bruce et al. | IEEE | 2016