An analysis of visual faces datasets

Abstract

This paper presents an analysis of datasets of images of human faces with annotated facial keypoints, which are important in human-machine interaction, and their comparison. Datasets are divided according to external conditions of the subject into two groups: datasets in laboratory conditions and in the wild data. Moreover, a quick review of the state-of-the-art methods for keypoints detection is provided. Existing methods are categorized into the following three groups according to the approach to the solution of the problem: top-down, bottom-up and their combination.