Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/96495
Full metadata record
DC FieldValueLanguage
dc.contributor.authorGeng, Congen
dc.contributor.authorJiang, Xudongen
dc.date.accessioned2013-11-05T06:26:48Zen
dc.date.accessioned2019-12-06T19:31:26Z-
dc.date.available2013-11-05T06:26:48Zen
dc.date.available2019-12-06T19:31:26Z-
dc.date.copyright2012en
dc.date.issued2012en
dc.identifier.citationGeng, C., & Jiang, X. (2013). Fully automatic face recognition framework based on local and global features. Machine Vision and Applications, 24(3), 537-549.en
dc.identifier.urihttps://hdl.handle.net/10356/96495-
dc.identifier.urihttp://hdl.handle.net/10220/17293en
dc.description.abstractFace 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.en
dc.language.isoenen
dc.relation.ispartofseriesMachine vision and applicationsen
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen
dc.titleFully automatic face recognition framework based on local and global featuresen
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.identifier.doi10.1007/s00138-012-0423-7en
item.fulltextNo Fulltext-
item.grantfulltextnone-
Appears in Collections:EEE Journal Articles

Google ScholarTM

Check

Altmetric

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.