scholarly journals Joint gender classification and age estimation by nearly orthogonalizing their semantic spaces

2018 ◽  
Vol 69 ◽  
pp. 9-21 ◽  
Author(s):  
Qing Tian ◽  
Songcan Chen
Keyword(s):  
Age Estimation ◽  
Gender Classification ◽  
Semantic Spaces

scholarly journals Accurate Age Estimation Using Multi-Task Siamese Network-Based Deep Metric Learning for Front Face Images

Symmetry ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 385 ◽  
Author(s):  
Yoosoo Jeong ◽  
Seungmin Lee ◽  
Daejin Park ◽  
Kil Park
Keyword(s):  
Age Estimation ◽  
Metric Learning ◽  
Front Face ◽  
Experimental Fact ◽  
Gender Classification ◽  
Learning Method ◽  
Siamese Network ◽  
Task Learning ◽  
Face Images ◽  
Deep Metric Learning

Recently, there have been many studies on the automatic extraction of facial information using machine learning. Age estimation from front face images is becoming important, with various applications. Our proposed work is based on the binary classifier, which only determines whether two input images are clustered in a similar class, and trains the convolutional neural networks (CNNs) model using the deep metric learning method based on the Siamese network. To converge the results of the training Siamese network, two classes, for which age differences are below a certain level of distance, are considered as the same class, so the ratio of positive database images is increased. The deep metric learning method trains the CNN model to measure similarity based on only age data, but we found that the accumulated gender data can also be used to compare ages. From this experimental fact, we adopted a multi-task learning approach to consider the gender data for more accurate age estimation. In the experiment, we evaluated our approach using MORPH and MegaAge-Asian datasets, and compared gender classification accuracy only using age data from the training images. In addition, from the gender classification, we found that our proposed architecture, which is trained with only age data, performs age comparison by using the self-generated gender feature. The accuracy enhancement by multi-task learning, for the simultaneous consideration of age and gender data, is discussed. Our approach results in the best accuracy among the methods based on deep metric learning on MORPH dataset. Additionally, our method is also the best results compared with the results of the state of art in terms of age estimation on MegaAge Asian and MORPH datasets.

Real-Time Gait-Based Age Estimation and Gender Classification from a Single Image

2021 ◽  
Author(s):  
Chi Xu ◽  
Yasushi Makihara ◽  
Ruochen Liao ◽  
Hirotaka Niitsuma ◽  
Xiang Li ◽  
...  
Keyword(s):  
Real Time ◽  
Age Estimation ◽  
Gender Classification ◽  
Single Image ◽  
And Gender

scholarly journals An Analysis on Gender Classification and Age Estimation Approaches

2017 ◽  
Vol 171 (10) ◽  
pp. 29-36
Author(s):  
Kanwal Deep ◽  
Preeti Rai
Keyword(s):  
Age Estimation ◽  
Gender Classification
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