Model based object recognition using stereo vision and geometric hashing

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    Abstract

    this paper we will show that the inherent robustness of geometric hashing to spurious data can be used to overcome the problems in stereo vision. The organisation of this paper is as follows. Section 2 discusses the geometric hashing technique and some previous work in this area. In section 3 we describe the stereo vision technique used. Section 4 shows some experimental results that prove the applicability of our method with real images and in section 5 we draw some overall conclusions and we discuss our future research interests.
    Original languageUndefined
    Number of pages6
    Publication statusPublished - 1996

    Keywords

    • IR-92547

    Cite this

    @conference{578fabde89334695944befa894b09d74,
    title = "Model based object recognition using stereo vision and geometric hashing",
    abstract = "this paper we will show that the inherent robustness of geometric hashing to spurious data can be used to overcome the problems in stereo vision. The organisation of this paper is as follows. Section 2 discusses the geometric hashing technique and some previous work in this area. In section 3 we describe the stereo vision technique used. Section 4 shows some experimental results that prove the applicability of our method with real images and in section 5 we draw some overall conclusions and we discuss our future research interests.",
    keywords = "IR-92547",
    author = "{van Dijck}, H.A.L. and {van der Heijden}, Ferdinand and Korsten, {Maarten J.}",
    year = "1996",
    language = "Undefined",

    }

    TY - CONF

    T1 - Model based object recognition using stereo vision and geometric hashing

    AU - van Dijck, H.A.L.

    AU - van der Heijden, Ferdinand

    AU - Korsten, Maarten J.

    PY - 1996

    Y1 - 1996

    N2 - this paper we will show that the inherent robustness of geometric hashing to spurious data can be used to overcome the problems in stereo vision. The organisation of this paper is as follows. Section 2 discusses the geometric hashing technique and some previous work in this area. In section 3 we describe the stereo vision technique used. Section 4 shows some experimental results that prove the applicability of our method with real images and in section 5 we draw some overall conclusions and we discuss our future research interests.

    AB - this paper we will show that the inherent robustness of geometric hashing to spurious data can be used to overcome the problems in stereo vision. The organisation of this paper is as follows. Section 2 discusses the geometric hashing technique and some previous work in this area. In section 3 we describe the stereo vision technique used. Section 4 shows some experimental results that prove the applicability of our method with real images and in section 5 we draw some overall conclusions and we discuss our future research interests.

    KW - IR-92547

    M3 - Paper

    ER -