Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/96495
Title: Fully automatic face recognition framework based on local and global features
Authors: Geng, Cong
Jiang, Xudong
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2012
Source: Geng, C., & Jiang, X. (2013). Fully automatic face recognition framework based on local and global features. Machine Vision and Applications, 24(3), 537-549.
Series/Report no.: Machine vision and applications
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.
URI: https://hdl.handle.net/10356/96495
http://hdl.handle.net/10220/17293
DOI: 10.1007/s00138-012-0423-7
Fulltext Permission: none
Fulltext Availability: No Fulltext
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