  The most frequently employed measure for performance characterisation of
local feature detectors is repeatability, but it has been observed that this
does not necessarily mirror actual performance. Presented are improved
repeatability formulations which correlate much better with the true
performance of feature detectors. Comparative results for several
state-of-the-art feature detectors are presented using these measures; it is
found that Hessian-based detectors are generally superior at identifying
features when images are subject to various geometric and photometric
transformations.
