On performance evaluation of face detection and localization algorithms
When comparing different methods for face detection or localization, one realizes that just simply comparing the reported results is misleading as, even if the results are reported on the same dataset, different authors have different views of what a correct detection/localization means. This paper addresses exactly this problem, proposing an objective measure for the goodness of a detection/localization for the case of frontal faces. The usage of the proposed technique insures a fair and unbiased way of reporting the results, making the experiment repeatable, measurable, and comparable by anybody else.