  It is human nature to give prime importance to facial appearances. Often, to
look good is to feel good. Also, facial features are unique to every individual
on this planet, which means it is a source of vital information. This work
proposes a framework named E-Pro for the detection and recognition of faces by
taking facial images as inputs. E-Pro has its potential application in various
domains, namely attendance, surveillance, crowd monitoring, biometric-based
authentication etc. E-Pro is developed here as a mobile application that aims
to aid lecturers to mark attendance in a classroom by detecting and recognizing
the faces of students from a picture clicked through the app. E-Pro has been
developed using Google Firebase Face Recognition APIs, which uses Euler Angles,
and Probabilistic Model. E-Pro has been tested on stock images and the
experimental results are promising.
