Can a Smile Reveal Your Gender?

Piotr Bilinski, Antitza Dantcheva, Francois Bremond
2016 2016 International Conference of the Biometrics Special Interest Group (BIOSIG)  
Automated gender estimation has numerous applications including video surveillance, human computer-interaction, anonymous customized advertisement and image retrieval. Most commonly, the underlying algorithms analyze facial appearance for clues of gender. In this work, we propose a novel approach for gender estimation, based on facial behavior in video-sequences capturing smiling subjects. The proposed behavioral approach quantifies gender dimorphism of facial smiling-behavior and is
more » ... r and is instrumental in cases of (a) omitted appearance-information (e.g. low resolution due to poor acquisition), (b) gender spoofing (e.g. makeup-based face alteration), as well as can be utilized to (c) improve the performance of appearance-based algorithms, since it provides complementary information. The proposed algorithm extracts spatio-temporal features based on dense trajectories, represented by a set of descriptors encoded by Fisher Vectors. Our results suggest that smile-based features include significant gender-clues. The designed algorithm obtains true gender classification rates of 86.3% for adolescents, significantly outperforming two state-of-the-art appearance-based algorithms (OpenBR and how-old.net), while for adults we obtain true gender classification rates of 91.01%, which is comparably discriminative to the better of these appearance-based algorithms.
doi:10.1109/biosig.2016.7736914 dblp:conf/biosig/BilinskiDB16 fatcat:pgfsrj22fvax3bqtmeza7qcyyi