Visual Vehicle Egomotion Estimation using the Fourier-Mellin Transform

Roland Goecke, Arkshay Asthana, Niklas Pettersson, Lars Petersson

    Research output: A Conference proceeding or a Chapter in BookConference contribution

    31 Citations (Scopus)

    Abstract

    This paper is concerned with the problem of estimating the motion of a single camera from a sequence of images, with an application scenario of vehicle egomotion estimation. Egomotion estimation has been an active area of research for many years and various solutions to the problem have been proposed. Many methods rely on optical flow or local image features to establish the spatial relationship between two images. A new method of egomotion estimation is presented which makes use of the Fourier-Mellin Transform for registering images in a video sequence, from which the rotation and translation of the camera motion can be estimated. The Fourier-Mellin Transform provides an accurate and efficient way of computing the camera motion parameters. It is a global method that takes the contributions from all pixels into account. The performance of the proposed approach is compared to two variants of optical flow methods and results are presented for a real-world video sequence taken from a moving vehicle
    Original languageEnglish
    Title of host publicationProceedings of the 2007 IEEE Intelligent Vehicles Symposium IV
    EditorsUrbano Nunes
    Place of PublicationAustralia
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages450-455
    Number of pages6
    ISBN (Print)9781424410675
    DOIs
    Publication statusPublished - 2007
    Event2007 IEEE Intelligent Vehicles Symposium IV - Istanbul, Istanbul, Turkey
    Duration: 13 Jun 200715 Jun 2007

    Conference

    Conference2007 IEEE Intelligent Vehicles Symposium IV
    CountryTurkey
    CityIstanbul
    Period13/06/0715/06/07

    Fingerprint

    Fourier transforms
    Optical flows
    Cameras
    Pixels

    Cite this

    Goecke, R., Asthana, A., Pettersson, N., & Petersson, L. (2007). Visual Vehicle Egomotion Estimation using the Fourier-Mellin Transform. In U. Nunes (Ed.), Proceedings of the 2007 IEEE Intelligent Vehicles Symposium IV (pp. 450-455). Australia: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/IVS.2007.4290156
    Goecke, Roland ; Asthana, Arkshay ; Pettersson, Niklas ; Petersson, Lars. / Visual Vehicle Egomotion Estimation using the Fourier-Mellin Transform. Proceedings of the 2007 IEEE Intelligent Vehicles Symposium IV. editor / Urbano Nunes. Australia : IEEE, Institute of Electrical and Electronics Engineers, 2007. pp. 450-455
    @inproceedings{b016824f149443dfbe6ca5ea48f2458b,
    title = "Visual Vehicle Egomotion Estimation using the Fourier-Mellin Transform",
    abstract = "This paper is concerned with the problem of estimating the motion of a single camera from a sequence of images, with an application scenario of vehicle egomotion estimation. Egomotion estimation has been an active area of research for many years and various solutions to the problem have been proposed. Many methods rely on optical flow or local image features to establish the spatial relationship between two images. A new method of egomotion estimation is presented which makes use of the Fourier-Mellin Transform for registering images in a video sequence, from which the rotation and translation of the camera motion can be estimated. The Fourier-Mellin Transform provides an accurate and efficient way of computing the camera motion parameters. It is a global method that takes the contributions from all pixels into account. The performance of the proposed approach is compared to two variants of optical flow methods and results are presented for a real-world video sequence taken from a moving vehicle",
    author = "Roland Goecke and Arkshay Asthana and Niklas Pettersson and Lars Petersson",
    year = "2007",
    doi = "10.1109/IVS.2007.4290156",
    language = "English",
    isbn = "9781424410675",
    pages = "450--455",
    editor = "Urbano Nunes",
    booktitle = "Proceedings of the 2007 IEEE Intelligent Vehicles Symposium IV",
    publisher = "IEEE, Institute of Electrical and Electronics Engineers",
    address = "United States",

    }

    Goecke, R, Asthana, A, Pettersson, N & Petersson, L 2007, Visual Vehicle Egomotion Estimation using the Fourier-Mellin Transform. in U Nunes (ed.), Proceedings of the 2007 IEEE Intelligent Vehicles Symposium IV. IEEE, Institute of Electrical and Electronics Engineers, Australia, pp. 450-455, 2007 IEEE Intelligent Vehicles Symposium IV, Istanbul, Turkey, 13/06/07. https://doi.org/10.1109/IVS.2007.4290156

    Visual Vehicle Egomotion Estimation using the Fourier-Mellin Transform. / Goecke, Roland; Asthana, Arkshay; Pettersson, Niklas; Petersson, Lars.

    Proceedings of the 2007 IEEE Intelligent Vehicles Symposium IV. ed. / Urbano Nunes. Australia : IEEE, Institute of Electrical and Electronics Engineers, 2007. p. 450-455.

    Research output: A Conference proceeding or a Chapter in BookConference contribution

    TY - GEN

    T1 - Visual Vehicle Egomotion Estimation using the Fourier-Mellin Transform

    AU - Goecke, Roland

    AU - Asthana, Arkshay

    AU - Pettersson, Niklas

    AU - Petersson, Lars

    PY - 2007

    Y1 - 2007

    N2 - This paper is concerned with the problem of estimating the motion of a single camera from a sequence of images, with an application scenario of vehicle egomotion estimation. Egomotion estimation has been an active area of research for many years and various solutions to the problem have been proposed. Many methods rely on optical flow or local image features to establish the spatial relationship between two images. A new method of egomotion estimation is presented which makes use of the Fourier-Mellin Transform for registering images in a video sequence, from which the rotation and translation of the camera motion can be estimated. The Fourier-Mellin Transform provides an accurate and efficient way of computing the camera motion parameters. It is a global method that takes the contributions from all pixels into account. The performance of the proposed approach is compared to two variants of optical flow methods and results are presented for a real-world video sequence taken from a moving vehicle

    AB - This paper is concerned with the problem of estimating the motion of a single camera from a sequence of images, with an application scenario of vehicle egomotion estimation. Egomotion estimation has been an active area of research for many years and various solutions to the problem have been proposed. Many methods rely on optical flow or local image features to establish the spatial relationship between two images. A new method of egomotion estimation is presented which makes use of the Fourier-Mellin Transform for registering images in a video sequence, from which the rotation and translation of the camera motion can be estimated. The Fourier-Mellin Transform provides an accurate and efficient way of computing the camera motion parameters. It is a global method that takes the contributions from all pixels into account. The performance of the proposed approach is compared to two variants of optical flow methods and results are presented for a real-world video sequence taken from a moving vehicle

    U2 - 10.1109/IVS.2007.4290156

    DO - 10.1109/IVS.2007.4290156

    M3 - Conference contribution

    SN - 9781424410675

    SP - 450

    EP - 455

    BT - Proceedings of the 2007 IEEE Intelligent Vehicles Symposium IV

    A2 - Nunes, Urbano

    PB - IEEE, Institute of Electrical and Electronics Engineers

    CY - Australia

    ER -

    Goecke R, Asthana A, Pettersson N, Petersson L. Visual Vehicle Egomotion Estimation using the Fourier-Mellin Transform. In Nunes U, editor, Proceedings of the 2007 IEEE Intelligent Vehicles Symposium IV. Australia: IEEE, Institute of Electrical and Electronics Engineers. 2007. p. 450-455 https://doi.org/10.1109/IVS.2007.4290156