DocumentCode :
1661848
Title :
Age estimation from human body images
Author :
Yongxin Ge ; Jiwen Lu ; Wu Fan ; Dan Yang
Author_Institution :
Sch. of Software Eng., Chongqing Univ., Chongqing, China
fYear :
2013
Firstpage :
2337
Lastpage :
2341
Abstract :
In this paper, we investigate the problem of estimating human ages from full body images. To our best knowledge, this problem has not been formally addressed before possibly due to the great challenges and lacking of such publicly available datasets. However, estimating human ages at a distance has a number of potential applications, especially for visual surveillance in such places as supermarkets, airports, building entrances, and shopping malls. In this paper, we propose a new human age estimation approach from full body images with frontal or back views. Our contributions are three-fold. First, we collect a human body image dataset containing 1500 public figures or celebrities searched from the internet, as well as the age label information of each image. Second, we explore several widely used human local appearance feature descriptors with a regression model to estimate human ages from these body images. Lastly, we apply a multiview canonical correlation analysis (MCCA) method by making use of multiple feature descriptors to exploit complementary information to further improve the age estimation performance. Experimental results have clearly demonstrated the feasibility of using fully body images to estimate human age and the efficacy of our proposed approach.
Keywords :
correlation methods; estimation theory; regression analysis; video surveillance; Internet; MCCA method; human age estimation approach; human body image dataset; human body imaging; human local appearance feature descriptor; multiple feature descriptor; multiview canonical correlation analysis method; regression model; visual surveillance; Computer vision; Conferences; Estimation; Face; Feature extraction; Pattern recognition; Standards; Age estimation; biometrics; multiple feature fusion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
ISSN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2013.6638072
Filename :
6638072
Link To Document :
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