Revolutionary Facial Recognition System
Many people use facial recognition systems every day to unlock their smartphones, play video games, or access their online bank accounts. However, current technology often requires bulky projectors and lenses. Researchers have now developed a sleeker 3D surface imaging system with simplified optics, as reported in ACS’ Nano Letters. In proof-of-concept demonstrations, the new system recognized the face of Michelangelo’s David just as effectively as an existing smartphone system.
How 3D Surface Imaging Works
3D surface imaging is a key component of smartphone facial recognition, as well as in computer vision and autonomous driving. These systems typically use a dot projector that contains a laser, lenses, a light guide, and a diffractive optical element (DOE). The DOE breaks the laser beam into an array of about 32,000 infrared dots, which are projected onto a person’s face. The device’s camera then reads the pattern created to confirm the identity. However, dot projector systems are relatively large, making them impractical for small devices like smartphones.
The New and Improved System
To address this issue, researchers replaced the traditional dot projector with a low-power laser and a flat gallium arsenide surface, significantly reducing the imaging device’s size and power consumption. They etched the top of the thin metallic surface with a nanopillar pattern, creating a metasurface that scatters light as it passes through the material. The low-powered laser light scatters into 45,700 infrared dots, which are then projected onto an object or face positioned in front of the light source. In tests, the new system accurately identified a 3D replica of Michelangelo’s David using five to 10 times less power and on a platform with a surface area about 230 times smaller than a common dot-projector system.
These findings demonstrate the potential of metasurfaces for effective small-scale low-power imaging solutions for facial recognition, robotics, and extended reality applications.
The authors acknowledge funding from Hon Hai Precision Industry, the National Science and Technology Council in Taiwan, and the Ministry of Education in Taiwan.