  Detecting and recognizing faces accurately has always been a challenge.
Differentiating facial features, training images, and producing quick results
require a lot of computation. The REaL system we have proposed in this paper
discusses its functioning and ways in which computations can be carried out in
a short period. REaL experiments are carried out on live images and the
recognition rates are promising. The system is also successful in removing
non-human objects from its calculations. The system uses a local database to
store captured images and feeds the neural network frequently. The captured
images are cropped automatically to remove unwanted noise. The system
calculates the Euler angles and the probability of whether the face is smiling,
has its left eye, and right eyes open or not.
