Title :
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
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;
Conference_Titel :
Image Information Processing (ICIIP), 2013 IEEE Second International Conference on
Conference_Location :
Shimla
Print_ISBN :
978-1-4673-6099-9
DOI :
10.1109/ICIIP.2013.6707668
