Face recognition using SURF features

Geng Du; Fei Su; Anni Cai

doi:10.1117/12.832636

30 October 2009 Face recognition using SURF features

Geng Du, Fei Su, Anni Cai

Proceedings Volume 7496, MIPPR 2009: Pattern Recognition and Computer Vision; 749628 (2009) https://doi.org/10.1117/12.832636
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

The Scale Invariant Feature Transform (SIFT) proposed by David G. Lowe has been used in face recognition and proved to perform well. Recently, a new detector and descriptor, named Speed-Up Robust Features (SURF) suggested by Herbert Bay, attracts people's attentions. SURF is a scale and in-plane rotation invariant detector and descriptor with comparable or even better performance with SIFT. Because each of SURF feature has only 64 dimensions in general and an indexing scheme is built by using the sign of the Laplacian, SURF is much faster than the 128-dimensional SIFT at the matching step. Thus based on the above advantages of SURF, we propose to exploit SURF features in face recognition in this paper.

Citation Download Citation

Geng Du, Fei Su, and Anni Cai "Face recognition using SURF features", Proc. SPIE 7496, MIPPR 2009: Pattern Recognition and Computer Vision, 749628 (30 October 2009); https://doi.org/10.1117/12.832636

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available