Gender-aided people recognition in photo collections

We show how to recognize people based on their faces in Consumer Photo Collections while also incorporating context in the form of gender information. We devise and explore a unified framework that has a graphical model along a distance-based face description method at its core. We jointly recognize people across an entire photo collection to also consider the specifics of photos that depict multiple people. Experiments on two datasets demonstrate and validate the effectiveness of our probabilistic approach compared to traditional methods that do not consider gender information.