CASIA OpenIR  > 模式识别国家重点实验室  > 生物识别与安全技术研究
Multi-label convolutional neural network based pedestrian attribute classification
Zhu, Jianqing1; Liao, Shengcai2; Lei, Zhen2; Li, Stan Z.2
Source PublicationIMAGE AND VISION COMPUTING
2017-02-01
Volume58Pages:224-229
SubtypeArticle
AbstractRecently, pedestrian attributes like gender, age, clothing etc., have been used as soft biometric traits for recognizing people. Unlike existing methods that assume the independence of attributes during their prediction, we propose a multi-label convolutional neural network(MLCNN) to predict multiple attributes together in a unified framework. Firstly, a pedestrian image is roughly divided into multiple overlapping body parts, which are simultaneously integrated in the multi-label convolutional neural network. Secondly, these parts are filtered independently and aggregated in the cost layer. The cost function is a combination of multiple binary attribute classification cost functions. Experiments show that the proposed method significantly outperforms the SVM based method on the PETA database. (C) 2016 Elsevier B.V. All rights reserved.
KeywordPedestrian Attribute Classification Multi-label Classification Convolutional Neural Network
WOS HeadingsScience & Technology ; Technology ; Physical Sciences
DOI10.1016/j.imavis.2016.07.004
WOS KeywordSOFT BIOMETRICS
Indexed BySCI
Language英语
Funding OrganizationScientific Research Funds of Huaqiao University(16BS108) ; National Natural Science Foundation of China(61602191 ; Chinese Academy of Sciences Project(KGZD-EW-102-2) ; 61375037 ; 61473291 ; 61572501 ; 61502491 ; 61572536)
WOS Research AreaComputer Science ; Engineering ; Optics
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Optics
WOS IDWOS:000395844700021
Citation statistics
Cited Times:9[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14433
Collection模式识别国家重点实验室_生物识别与安全技术研究
Affiliation1.Huaqiao Univ, Coll Engn, Quanzhou 362021, Fujian, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Ctr Biometr & Secur Res, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Zhu, Jianqing,Liao, Shengcai,Lei, Zhen,et al. Multi-label convolutional neural network based pedestrian attribute classification[J]. IMAGE AND VISION COMPUTING,2017,58:224-229.
APA Zhu, Jianqing,Liao, Shengcai,Lei, Zhen,&Li, Stan Z..(2017).Multi-label convolutional neural network based pedestrian attribute classification.IMAGE AND VISION COMPUTING,58,224-229.
MLA Zhu, Jianqing,et al."Multi-label convolutional neural network based pedestrian attribute classification".IMAGE AND VISION COMPUTING 58(2017):224-229.
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