  This article explores a face recognition alternative which seeks to
contribute to resolve current security vulnerabilities in most recognition
architectures. Current low cost facial authentication software in the market
can be fooled by a printed picture of a face due to the lack of depth
information. The presented software creates a depth map of the face with the
help of a stereo setup, offering a higher level of security than traditional
recognition programs. Analysis of the person's identity and facial depth map
are processed through deep convolutional neural networks, providing a secure
low cost real-time face authentication method.
