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Muti-stage learning for gender and age prediction
Fang, Jie1,2; Yuan, Yuan3; Lu, Xiaoqiang1; Feng, Yachuang1
Department光学影像学习与分析中心
2019-03-21
Source PublicationNEUROCOMPUTING
ISSN0925-2312;1872-8286
Volume334Pages:114-124
Contribution Rank1
Abstract

Automatic gender and age prediction has become relevant to an increasing amount of applications, particularly under the rise of social platforms and social media. However, the performances of existing methods on real-world images are still not satisfactory as we expected, especially when compared to that of face recognition. The reason is that, facial images for gender and age prediction have inherent small inter-class and big intra-class differences, i.e., two images with different skin colors and same age category label have big intra-class difference. However, most existing methods have not constructed discriminative representations for digging out these inherent characteristics very well. In this paper, a method based on muti-stage learning is proposed: The first stage is marking the object regions with an encoder-decoder based segmentation network. Specifically, the segmentation network can classify each pixel into two classes, "people" and others, and only the "people" regions are used for the subsequent processing. The second stage is precisely predicting the gender and age information with the proposed prediction network, which encodes global information, local region information and the interactions among different local regions into the final representation, and then finalizes the prediction. Additionally, we evaluate our method on three public and challenging datasets, and the experimental results verify the effectiveness of our proposed method. (C) 2019 Elsevier B.V. All rights reserved.

KeywordGender and age prediction Muti-stage learning Segmentation network
DOI10.1016/j.neucom.2018.12.073
Indexed BySCI
Language英语
WOS IDWOS:000458626300011
PublisherELSEVIER SCIENCE BV
Citation statistics
Document Type期刊论文
Identifierhttp://ir.opt.ac.cn/handle/181661/31158
Collection光学影像学习与分析中心
Corresponding AuthorLu, Xiaoqiang
Affiliation1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Key Lab Spectral Imaging Technol CAS, Xian 710119, Shaanxi, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Northwestern Polytech Univ, Ctr Opt Imagery Anal & Learning OPTIMAL, Xian 710072, Shaanxi, Peoples R China
Recommended Citation
GB/T 7714
Fang, Jie,Yuan, Yuan,Lu, Xiaoqiang,et al. Muti-stage learning for gender and age prediction[J]. NEUROCOMPUTING,2019,334:114-124.
APA Fang, Jie,Yuan, Yuan,Lu, Xiaoqiang,&Feng, Yachuang.(2019).Muti-stage learning for gender and age prediction.NEUROCOMPUTING,334,114-124.
MLA Fang, Jie,et al."Muti-stage learning for gender and age prediction".NEUROCOMPUTING 334(2019):114-124.
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