Open AccessPartially Occluded Face Recognition using Dynamic Time Wrapping
Author(s) -
Ashish Kumar,
P. Shanmugavadivu
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.22.11804
Subject(s) - artificial intelligence , computer science , pattern recognition (psychology) , face (sociological concept) , feature (linguistics) , facial recognition system , similarity (geometry) , computer vision , image (mathematics) , annotation , domain (mathematical analysis) , mathematics , social science , sociology , mathematical analysis , linguistics , philosophy
It is evident that the research contributions in the domain of partially occluded image are quite sparse. This paper presents a novel method, termed as Partially Occluded Face Recognition (POFR) using Maximally Stable External Regions (MSER) feature sets and Dynamic Time Wrapping (DTW). This proposed system works in two phases: Phase-I, creates an annotated database using the non-occluded images, and Phase-II focuses on the detection and recognition of partially occluded probe image, which is also annotated using the mechanism of phase-I. Hence, POFR selectively and dynamically calibrates the annotated database as per the annotation of the probe image. Further, the similarity between the feature sets of the annotated database images and the probe image is computed, using the principle of DTW. The POFR is tested on the face images from University of Stirling dataset and the average accuracy of face recognition is recorded as 88%. This method promises a computational advantage for partially occluded face recognition without any prior reconstruction or synthesis. The POFR finds direct applications in surveillance and security systems.