Facial features for gender recognition
Guangjun Liao, Wei Chen, Yaoxin Wu · 2016
Facial features are complex data sets including both personal features and common features. Gender recognition based on facial features is a study on common features of facial features, and has already been a research focus nowadays for its wide applications. Referring to achievements of facial measurement, we used the depth gradient and the distance of facial features based on two-dimensional and three-dimensional information of human face as feature inputs, and trained the gender recognition model utilizing the random forest algorithm. We tested it on public facial database and small-scale independently collected 3D facial database, and the result of the experiment was satisfactory. Besides, the performance of the algorithm under the circumstances of feature missing was also valued in this paper.