Paper
18 November 2013 GUCLF: a new light field face database
R. Raghavendra, Kiran B. Raja, Bian Yang, Christoph Busch
Author Affiliations +
Proceedings Volume 8785, 8th Iberoamerican Optics Meeting and 11th Latin American Meeting on Optics, Lasers, and Applications; 8785DB (2013) https://doi.org/10.1117/12.2026184
Event: 8th Ibero American Optics Meeting/11th Latin American Meeting on Optics, Lasers, and Applications, 2013, Porto, Portugal
Abstract
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).
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
R. Raghavendra, Kiran B. Raja, Bian Yang, and Christoph Busch "GUCLF: a new light field face database", Proc. SPIE 8785, 8th Iberoamerican Optics Meeting and 11th Latin American Meeting on Optics, Lasers, and Applications, 8785DB (18 November 2013); https://doi.org/10.1117/12.2026184
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Cameras

Databases

Facial recognition systems

Sensors

Surveillance

Detection and tracking algorithms

Digital cameras

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