Face recognition technology that works in the dark

Science Daily  April 16, 2018
Researchers at the U.S. Army Research Laboratory used advanced domain adaptation techniques based on deep neural networks to overcome the challenge of cross-spectrum, or heterogeneous, face recognition to process thermal image of a person’s face captured in low-light or nighttime conditions. The fundamental approach is composed of two key parts: a non-linear regression model that maps a given thermal image into a corresponding visible latent representation and an optimization problem that projects the latent projection back into the image space. In face verification experiments using a common open source deep neural network architecture, their approach achieved better verification performance than a generative adversarial network-based approach… read more.

A conceptual illustration for thermal-to-visible synthesis for interoperability with existing visible-based facial recognition systems. Credit: Courtesy Eric Proctor, William Parks and Benjamin S. Riggan

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