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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 isdoi:10.1109/biosig.2016.7736914 dblp:conf/biosig/BilinskiDB16 fatcat:pgfsrj22fvax3bqtmeza7qcyyi