Multi-label convolutional neural network based pedestrian attribute classification | |
Zhu, Jianqing1; Liao, Shengcai2![]() ![]() ![]() | |
发表期刊 | IMAGE AND VISION COMPUTING
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2017-02-01 | |
卷号 | 58页码:224-229 |
文章类型 | Article |
摘要 | Recently, 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. |
关键词 | Pedestrian Attribute Classification Multi-label Classification Convolutional Neural Network |
WOS标题词 | Science & Technology ; Technology ; Physical Sciences |
DOI | 10.1016/j.imavis.2016.07.004 |
关键词[WOS] | SOFT BIOMETRICS |
收录类别 | SCI |
语种 | 英语 |
项目资助者 | Scientific 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研究方向 | Computer Science ; Engineering ; Optics |
WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Optics |
WOS记录号 | WOS:000395844700021 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/14433 |
专题 | 模式识别国家重点实验室_生物识别与安全技术研究 |
作者单位 | 1.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 |
推荐引用方式 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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JQZHU-IVC-2017.pdf(1036KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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