Download our whitepaper on
"Automotive In-Cabin Face Recognition and Anti-Spoofing AI using 3D Time of Flight Camera".
MulticoreWare and Melexis have jointly worked on a new face understanding algorithm with modules such as face detection & recognition, drowsiness / distraction detection and anti-spoofing detection. Check out our whitepaper focussing on the findings from implementing custom neural networks on the Melexis ToF sensor.
Automotive cabin sensing is a rapidly evolving area with a range of applications using a combination of sensors and intelligent algorithms. A robust Driver Monitoring System (DMS) is an essential component of Euro NCAP regulations, and the most widely adopted systems today are RGB Camera-based. RGB cameras demonstrate a great promise in modelling driver behaviour, but have issues with illumination changes, occlusions, and anti-spoofing functionality.
As AI technology advances, so does sensor technology, with indirect Time of Flight cameras being a prominent example (iToF) of 3D sensing. An iToF sensor can provide 2D amplitude images and distance images, giving it the advantage of being resilient to ambient lighting, low-contrast scenes and provides accurate depth information.
MulticoreWare will present our findings from implementing custom neural networks on the Melexis MLX 75027 VGA ToF sensor and demonstrate the efficiency for modules such as Face Detection and Face Recognition that enable applications like Driver Authentication, Drowsiness Detection, etc.
Furthermore, we will illustrate iToF cameras’ superior ability to detect Anti-Spoofing (2D Print Attack) leveraging the distance images.