Abstract

Facial detection usually comes first in face recognition and face analysis systems. Previously, techniques such as directed gradient histograms and cascades relied on manually-engineered features from particular photos. Nevertheless, the precision with which these techniques could identify faces in uncontrolled environments was restricted. Numerous deep learning-based face recognition frameworks have recently been developed, many of which have significantly increased accuracy, as a result of the rapid progress of deep learning in computer vision. Despite these advancements, detecting small, scaled, positioned, occluded, blurred, and faces that are partially occluded in uncontrolled conditions remains a challenge in face identification. This problem has been studied for many years but has not been completely resolved.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call