GENDER CLASSIFICATION FROM FACE IMAGES WITH LOCAL TEXTURE PATTERN
Yi-Jui Li, Chih‐Chin Lai, Chih‐Hung Wu, Shing‐Tai Pan, Shie-Jue Lee · 2015
Recognizing human gender automatically by a computer is a challenging problem. It has been attracting research attention due to its wide real-life applications. Gender classification can be viewed as an essential preprocessing step in face recognition. Because human faces contain a lot of really useful information, many approaches based on facial features have been investigated for gender classification. In this paper, we present a novel texture pattern as feature descriptor to identify the gender from the facial images. The classification is performed by using a support vector machine. Experimental results on the FERET database are provided to illustrate the proposed approach is an effective method, compared to other similar methods.