@CONFERENCE\{IMM2010-05929,
    author       = "H. Aan{\ae}s and A. L. Dahl and K. S. Pedersen",
    title        = "On Recall Rate of Interest Point Detectors",
    year         = "2010",
    month        = "jun",
    keywords     = "Interst point detectors,",
    booktitle    = "Electronic Proceedings of {3DPVT'}10, the Fifth International Symposium on {3D} Data Processing, Visualization and Transmission",
    volume       = "",
    series       = "",
    editor       = "",
    publisher    = "",
    organization = "",
    address      = "",
    url          = "http://campwww.informatik.tu-muenchen.de/3DPVT2010/data/media/e-proceeding/session07.html#paper97",
    abstract     = "In this paper we provide a method for evaluating interest point detectors independently of image descriptors. This is possible because we have compiled a unique data set enabling us to determine if common interest points are found. The data contains 60 scenes of a wide range of object types, and for each scene we have 119 precisely located camera positions obtained from a camera mounted on an industrial robot arm. The scene surfaces have been scanned using structured light, providing precise {3D} ground truth. We have investigated a number of the most popular interest point detectors. This is done in relation to the number of interest points, the recall rate as a function of camera position and light variation, and the sensitivity relative to model parameter change. The overall conclusion is that the Harris corner detector has a very high recall rate, but is sensitive to change in scale. The Hessian corners perform overall well followed by {MSER} (Maximally Stable Extremal Regions), whereas the {FAST} corner detector, {IBR} (Intensity Based Regions) and {EBR} (Edge Based Regions) performs poorly. Furthermore, the repeatability of the corner detectors is quite unaffected by the parameter setting, and only the number of interest points change."
}