NDLI: Fully automatic face recognition framework based on local and global features

Content Provider	Springer Nature Link
Author	Geng, Cong Jiang, Xudong
Copyright Year	2012
Abstract	Face recognition algorithms can be divided into two categories: holistic and local feature-based approaches. Holistic methods are very popular in recent years due to their good performance and high efficiency. However, they depend on careful positioning of the face images into the same canonical pose, which is not an easy task. On the contrary, some local feature-based approaches can achieve good recognition performances without additional alignment. But their computational burden is much heavier than holistic approaches. To solve these problems in holistic and local feature-based approaches, we propose a fully automatic face recognition framework based on both the local and global features. In this work, we propose to align the input face images using multi-scale local features for the holistic approach, which serves as a filter to narrow down the database for further fine matching. The computationally heavy local feature-based approach is then applied on the narrowed database. This fully automatic framework not only speeds up the local feature-based approach, but also improves the recognition accuracy comparing with the holistic and local approaches as shown in the experiments.
Starting Page	537
Ending Page	549
Page Count	13
File Format	PDF
ISSN	09328092
Journal	Machine Vision and Applications
Volume Number	24
Issue Number	3
e-ISSN	14321769
Language	English
Publisher	Springer-Verlag
Publisher Date	2012-03-22
Publisher Place	Berlin/Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Face alignment Face recognition Holistic approach Multi-scale local feature Pattern Recognition Image Processing and Computer Vision Communications Engineering, Networks
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Computer Science Applications Software Hardware and Architecture

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