Abstract
This paper describes a face recognition algorithm using feature points of face parts, which is classified as a feature-based method. As recognition performance depends on the combination of extracted feature points, we utilize all reliable feature points effectively. From moving video input, well-conditioned face images with a frontal direction and without facial expression are extracted. To select such well-conditioned images, an iteratively minimizing variance method is used with variable input face images. This iteration drastically brings convergence to the minimum variance of 1 for a quarter to an eighth of all data, which proves to take the frontal image in 0.27 second from video at most. The proposed system using six statistic values realizes 98.3% as an authentication rate.
Original language | English |
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Pages (from-to) | 29-44 |
Number of pages | 16 |
Journal | International Journal of Computer Science and Applications |
Volume | 13 |
Issue number | 2 |
Publication status | Published - 2016 |
Keywords
- Distance
- Distribution
- Face recognition
- Feature point
ASJC Scopus subject areas
- Computer Science Applications