Authors: George Toderici Sean M O’Malley George Passalis Theoharis Theoharis Ioannis A Kakadiaris
Publish Date: 2010/04/28
Volume: 89, Issue: 2-3, Pages: 382-391
Abstract
While the retrieval of datasets from human subjects based on demographic characteristics such as gender or race is an ability with wideranging application it remains poorlystudied In contrast a large body of work exists in the field of biometrics which has a different goal the recognition of human subjects Due to this disparity of interest existing methods for retrieval based on demographic attributes tend to lag behind the more wellstudied algorithms designed purely for face matching The question this raises is whether a face recognition system could be leveraged to solve these other problems and if so how effective it could be In the current work we explore the limits of such a system for gender and ethnicity identification given 1 a ground truth of demographicallylabeled textureless 3D models of human faces and 2 a stateoftheart facerecognition algorithm Once trained our system is capable of classifying the gender and ethnicity of any such model of interest Experiments are conducted on 4007 facial meshes from the benchmark Face Recognition Grand Challenge v2 dataset
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