Title :
Eigenfaces for Face Detection: A Novel Study
Author :
Alakkari, Salaheddin ; Collins, J.J.
Author_Institution :
Dept. of Comput. Sci. & Inf. Syst., Univ. of Limerick, Limerick, Ireland
Abstract :
A study is presented on face detection using Principal Component Analysis as a paradigm for generating compact representation for the human face. The study will focus on the contribution of individual eigenfaces in the face-space for classification in order to extract a minimum encoding for very low resolution images. The fourth, sixth, and seventh eigenfaces are identified as being particularly critical for classification, with the lowest order eigenface having a significant discriminatory contribution.
Keywords :
eigenvalues and eigenfunctions; face recognition; image classification; image representation; image resolution; principal component analysis; compact representation; discriminatory contribution; eigenfaces; face detection; human face; image classification; low resolution images; principal component analysis; Covariance matrices; Eigenvalues and eigenfunctions; Face; Face detection; Image reconstruction; Principal component analysis; Training; Principal Component Analysis; classification; eigenfaces; face detection; last eigenface;
Conference_Titel :
Machine Learning and Applications (ICMLA), 2013 12th International Conference on
Conference_Location :
Miami, FL
DOI :
10.1109/ICMLA.2013.63
