Image Generation Using Bidirectional Integral Features for Face Recognition with a Single Sample per Person

Title
Image Generation Using Bidirectional Integral Features for Face Recognition with a Single Sample per Person
Author
이민식
Keywords
ONE TRAINING IMAGE; ILLUMINATION; CLASSIFICATION; EXTRACTION; SELECTION; VECTORS; POSE
Issue Date
2015-09
Publisher
PUBLIC LIBRARY SCIENCE
Citation
PLOS ONE, v. 10, No. 9, Article ID e0138859
Abstract
In face recognition, most appearance-based methods require several images of each person to construct the feature space for recognition. However, in the real world it is difficult to collect multiple images per person, and in many cases there is only a single sample per person (SSPP). In this paper, we propose a method to generate new images with various illuminations from a single image taken under frontal illumination. Motivated by the integral image, which was developed for face detection, we extract the bidirectional integral feature (BIF) to obtain the characteristics of the illumination condition at the time of the picture being taken. The experimental results for various face databases show that the proposed method results in improved recognition performance under illumination variation.
URI
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0138859http://hdl.handle.net/20.500.11754/43767
ISSN
1932-6203
DOI
10.1371/journal.pone.0138859
Appears in Collections:
COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > ELECTRICAL ENGINEERING(전자공학부) > Articles
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE