DocumentCode
1947461
Title
A new face descriptor using local un-quantized patterns
Author
Mariappan, V.V. ; Jadhav, R.A. ; Sharma, P.B.
Author_Institution
2012 Labs., Huawei, Bangalore, India
fYear
2013
fDate
7-8 Feb. 2013
Firstpage
318
Lastpage
321
Abstract
We present a novel face representation based on local un-quantized patterns (LUP) descriptors. LUP descriptor is a simple yet powerful descriptor which measures the difference of intensities between surrounding pixel with the center in a local neighborhood, but preserves the finer local geometric structure unlike LBP, SIFT or HOG (which uses either the quantized version of local gray level patterns or quantized codes of image gradients). This descriptor also solves the problem of limited spatial support of LBP like operators, where increasing the size of local-neighborhood increases the histogram dimensions exponentially making it unsuitable for real-time needs. By applying principal component analysis (PCA) to LUP, we develop a new srepresentation, which gives better performance than LBP and comparable performance to LARK while only taking a fraction of the computation when compared to the latter.
Keywords
face recognition; image classification; image representation; principal component analysis; LBP like operators; LUP descriptors; PCA; face descriptor; face representation; geometric structure; histogram dimensions; local unquantized patterns; principal component analysis; Computer vision; Face; Face recognition; Histograms; Principal component analysis; Training; Face verification; local binary patterns (LBP); locally adaptive regression kernels (LARK);
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing Image Processing & Pattern Recognition (ICSIPR), 2013 International Conference on
Conference_Location
Coimbatore
Print_ISBN
978-1-4673-4861-4
Type
conf
DOI
10.1109/ICSIPR.2013.6497948
Filename
6497948
Link To Document