Title
Selecting discriminative CLBP patterns for age estimation
Abstract
Face analysis is of great interest in the context of digital signage to understand soft biometric of a person. Among the others information gathered from a face, the age of a person is still an open challenging problem. Face representation takes an important role for real time age discrimination. LBP descriptor and the related variants (e.g., CLBP) have been demonstrated to obtain the state-of-the-art performances in this field. In this paper, building on the CLBP representation, we propose a method to select the most discriminative CLBP patterns to represent faces for age classification. Experiments confirm that the proposed method improves the age classification accuracy by reducing computational costs both in terms of space and time.
Year
DOI
Venue
2015
10.1109/ICMEW.2015.7169755
2015 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)
Keywords
Field
DocType
Digital Signage,Age Estimation,Feature Selection
Computer vision,Feature selection,Pattern recognition,Computer science,Digital signage,Speech recognition,Artificial intelligence,Discriminative model
Conference
ISSN
Citations 
PageRank 
2330-7927
6
0.47
References 
Authors
19
4
Name
Order
Citations
PageRank
Alessandro Torrisi161.49
Giovanni Maria Farinella241257.13
Giovanni Puglisi338331.62
Sebastiano Battiato465978.73