GUCLF: a new light field face database
Raghavendra Ramachandra, Kiran Bylappa Raja, Bian Yang, Christoph Busch · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2013
The advancement in face recognition algorithm has a strong relationship with the availability of face databases that exhibit varying factors reflecting real life scenarios. The GUCLF face database is the first of its kind that can strongly influence the advancement in face recognition technology. In this paper, we introduce and describe our new face samples database collected using Lytro light field camera. The database consists of 200 reference samples and 303 probe samples collected from 25 subjects. The reference samples are collected in the controlled conditions using Canon EOS 550D DSLR camera. While probe samples are captured using both conventional digital camera (Sony DSC-S750) and Lytro light field camera. The probe samples are captured in three different scenarios: indoor, corridor and outdoor to include all possible real life conditions. In addition to the database description, this paper also elaborates on possible uses of the collected database and proposes a testing protocol. Further, we also present the quantitative results from the baseline experiments using the Kernel Discriminant Analysis (KDA).