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 :
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