Edge AI Face Recognition for Public Transport Fare Payment
Loading...
Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
TechRxiv
Abstract
Face Recognition technology is chiefly concerned
with accurately re-identifying individuals through the use of
mathematical face representations. It presents a window of
opportunity for the introduction of a fast, automated, seamless
and easy to deploy form of biometric technology. In this research
we design a fast, easy to use, and privacy oriented contactless
payment system for public transportation that chiefly makes
use of face recognition and internet of things technologies. We
demonstrate a one-shot face recognition model and also prepare
and test it for real-time inference on the edge.
Our system makes use of a Siamese Model built on top of the
Inception-Resnet V1 architecture with accuracy, precision and
recall values of 93.81%, 90.91% and 97.35% on our validation
set.
The model was deployed on a Raspberry Pi 4 Model B with an
Intel Neural Compute Stick 2. Inference was performed through
the inference engine API of the OpenVINO toolkit on the Neural
Compute Stick plugged into the Raspberry Pi.
The system is composed of three other subsystems, i.e. the edge
device, cloud database and user interface subsystems which work
together to ensure that payment is complete in under 2 seconds.
Description
Keywords
Siamese Network, Edge device, Face Recognition, Payment system
Citation
Rusoke, Blaise Marvin; Musinguzi, Denis; Miyingo, Simon Peter; Katumba, Andrew (2022): Edge AI Face Recognition for Public Transport Fare Payment. TechRxiv. Preprint. https://doi.org/10.36227/techrxiv.21432000.v1