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.