Poliface: A Multi-pose Synchronous Imaging System

Viet-Bac Nguyen, Van-Lieu Vu, Duc-Toan Truong, Viet-Anh Dao, Dang-Ha Nguyen, Thom Tran, Van-Xiem Hoang, Hoang-Anh The Nguyen

Abstract


To enhance the accuracy of face recognition technology in real-world scenarios, it is necessary to train deep learning models on datasets that contain a large number of labeled human face images under multiple poses, lighting, and accessory variations. In this paper, we introduce a novel acquisition system named the Poliface. This system can capture multiple high-resolution images simultaneously around the human head. We designed this system with a well-built aluminum structure, control electronic circuits, and high-performing in-house software. The results demonstrate the precise operation and exceptional stability of this system. Using this Poliface system, we have collected over 6 million photos, which can be used to train and evaluate facial recognition models, and exploited for three-dimensional (3D) virtual face reconstruction.

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References


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DOI: http://dx.doi.org/10.21553/rev-jec.361

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