Face recognition using gradient based local feature matching

Author

Nigam, Jyoti ; Gandhi, Thulasidharan

Author_Institution

Dept. of CSE, Krishna Inst. of Technol. (KIOT), Kanpur, India

fYear

2013

fDate

9-11 Dec. 2013

Firstpage

623

Lastpage

628

Abstract

In this paper a measure that computes dissimilarity score is proposed that can be used to find out the distance between two face samples. Gradient Binary Pattern are applied over face samples to transform them into some robust representation. Later corner features are extracted and they are tracked using KL-tracking and the number of unsuccessfully tracked corners are counted between each testing and training images. Four publicly available face databases are used for system testing, viz. YALE, BERN, ORL, CALTECH.

Keywords

face recognition; feature extraction; gradient methods; image matching; image representation; BERN; CALTECH; KL-tracking; ORL; YALE; corner feature extraction; dissimilarity score; face databases; face recognition; gradient based local feature matching; gradient binary pattern; robust image representation; system testing; training images; Databases; Face; Face recognition; Feature extraction; Lighting; Robustness; Testing; background; edgemap; expression; face recognition; gradient; illumination;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Information Processing (ICIIP), 2013 IEEE Second International Conference on

Conference_Location

Shimla

Print_ISBN

978-1-4673-6099-9

Type

conf

DOI

10.1109/ICIIP.2013.6707668

Filename

6707668