Pattern Based Gender Classification (original) (raw)
Various methods of Gender classification have been reported in various papers. Gender classification is one of the fundamental face analysis task. Automated gender classification is a most significant research area. Gender classification offers several industrial applications in future like monitoring, surveillance, commercial profiling and human computer interaction. There are different methods have been proposed for gender classification such as gait, iris, hand shape and hair. However, major techniques used for gender classification based on facial information. In this paper, we target a comparative study of gender classification using different existing techniques used for gender classification and focused on major strengths and limitations of these existing gender classification techniques like LDP, LBP, and PCA etc. This pattern study presents several future research areas in the domain of gender classification.