Automated evaluation of interest point detectors

Simon Lang, Martin Luerssen, David Powers

    Research output: Contribution to conferencePaperpeer-review

    2 Citations (Scopus)


    Interest point detectors are important components in a variety of computer vision systems. This paper demonstrates an automated virtual 3D environment for controlling and measuring detected interest points on 2D images in an accurate and rapid manner. Real-time affine transform tools enable easy implementation and full automation of complex scene evaluations without the time-cost of a manual setup. Nine detectors are tested and compared using evaluation and testing methods based on Schmid [18]. Each detector is tested on the BSDS500 image set using rotation in the X, Y, and Z axis as well as scale in the X, Y axis. Results demonstrate the differing performance and behaviour of each detector across the evaluated transformations, which may assist computer vision practitioners in choosing the right detector for their application.

    Original languageEnglish
    Number of pages5
    Publication statusPublished - 31 Oct 2013
    Event2013 IEEE/ACIS 12th International Conference on Computer and Information Science -
    Duration: 16 Jun 2013 → …


    Conference2013 IEEE/ACIS 12th International Conference on Computer and Information Science
    Period16/06/13 → …


    • Automated processing
    • Interest points
    • Repeatability
    • Visual Processing


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