Multi-Spectral Facial Biometrics in Access Control
This work addresses incremental improvements in biometric authentication for access control and healthcare systems, with potential benefits for security and medical applications.
The study tackled improving facial biometrics for access control by using multi-spectral sensors (RGB, depth, infrared) to select frontal-view frames, enhancing face recognition efficiency and temperature estimation. It reported emerging applications in biomedical and healthcare, such as contactless interfaces for surgery and rehabilitation.
This study demonstrates how facial biometrics, acquired using multi-spectral sensors, such as RGB, depth, and infrared, assist the data accumulation in the process of authorizing users of automated and semi-automated access systems. This data serves the purposes of person authentication, as well as facial temperature estimation. We utilize depth data taken using an inexpensive RGB-D sensor to find the head pose of a subject. This allows the selection of video frames containing a frontal-view head pose for face recognition and face temperature reading. Usage of the frontal-view frames improves the efficiency of face recognition while the corresponding synchronized IR video frames allow for more efficient temperature estimation for facial regions of interest. In addition, this study reports emerging applications of biometrics in biomedical and health care solutions. Including surveys of recent pilot projects, involving new sensors of biometric data and new applications of human physiological and behavioral biometrics. It also shows the new and promising horizons of using biometrics in natural and contactless control interfaces for surgical control, rehabilitation and accessibility.