Masked Face Detection using the Viola Jones Algorithm: A Progressive Approach for less Time Consumption

Abstract

The use of CCTV surveillance is today’s need in
public and private sector for ensuring security against terrorism
and robbery. Regular expressions are used to signify enormous
sets of motion attributes captured in video. The video vigilance
is popular system without using human interference to capture
important scenes. The motive of the work is to introduce automatic
revelation of masked objects in real time with a surveillance
camera. The main aim is to detect masked person automatically
in less time period. In this paper,the researcher proposes a system
that consists methods which uses four variant steps that are the
steps of calculating distance range of person from the camera,
eye or vision line detection and face part detection such as
mouth detection and face detection. Performance of proposed
algorithm is carried out on various real time inputs. Experimental
evaluation shows that proposed algorithm exceeds better in terms
of time consumption. This unique approach for the problem
has created a method transparent and easier in complexity so
that the real time implementation can be made beneficial and
workable. Analysis of the algorithms fulfillment on the test video
track gives appropriate judgments for additional improvements
in the masked face detection performance. Finally, based on the
research, the axioms were useful for the work which can be
usually accessible from available algorithms.