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Un-supervised and semi-supervised hand segmentation in egocentric images with noisy label learning

文献类型：期刊论文

作者Li, Yinlin1,2; Jia, Lihao3,4; Wang, Zidong5; Qian, Yang3,6; Qiao, Hong1,6,7,8
刊名NEUROCOMPUTING
出版日期2019-03-21
卷号334页码:11-24
关键词Hand segmentation Un-supervised Semi-supervised Deep convolutional neural network Noisy label
ISSN号0925-2312
DOI10.1016/j.neucom.2018.12.010
通讯作者Qiao, Hong(hong.qiao@ia.ac.cn)
英文摘要With the rapid development of wearable devices and technologies, hand segmentation remains a less explored direction in egocentric vision, which is very important for activity recognition, rehabilitation, robot self-learning, etc. To overcome the high cost of auxiliary equipment and pixel-level annotations, we present an un-supervised hand segmentation method for egocentric images. Firstly, a fully convolutional neural network (FCN) is pre-trained in source dataset containing pixel-level annotations. Then, in target dataset without labels, the network is re-trained with optimized masks, which are produced by modified local and global consistency learning (LLGC) based on pre-segmentation and superpixel features. Finally, hand segmentation is realized in an alternative way. Furthermore, to balance segmentation accuracy and the cost on labeling, we propose a new semi-supervised image segmentation framework with three subnets based on the optimized noisy masks and a small number of clean labeled data. Experimental results in two target datasets indicate that the proposed methods could achieve better performance than other methods. (C) 2019 Elsevier B.V. All rights reserved.
WOS关键词RECOGNITION ; ALGORITHM ; GESTURE
资助项目National Key Research and Development Program of China[2017YFB1300200] ; National Key Research and Development Program of China[2017YFB1300203] ; National Natural Science Foundation of China (NSFC)[U1713201] ; National Natural Science Foundation of China (NSFC)[U1613213] ; National Natural Science Foundation of China[61702516] ; National Natural Science Foundation of China[51705515] ; National Natural Science Foundation of China[61502494] ; National Natural Science Foundation of China[61627808] ; National Natural Science Foundation of China[91648205] ; National Natural Science Foundation of China[61702323] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32000000] ; development of science and technology of Guangdong province special fund project[2016B090910001]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000458626300002
出版者ELSEVIER SCIENCE BV
资助机构National Key Research and Development Program of China ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China ; Strategic Priority Research Program of Chinese Academy of Science ; development of science and technology of Guangdong province special fund project
源URL[http://ir.ia.ac.cn/handle/173211/25040]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组
通讯作者Qiao, Hong
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Beijing Key Lab Res & Applicat Robot Intelligence, Beijing 100190, Peoples R China
3.Chinese Acad Sci, Res Ctr Brain Inspired Intelligence, Inst Automat, Beijing 100190, Peoples R China
4.Chinese Acad Sci, Cloud Comp Ctr, Dongguan 523808, Peoples R China
5.Brunel Univ, Dept Informat Syst & Comp, Uxbridge UB8 3PH, Middx, England
6.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
7.Univ Sci & Technol Beijing, Sch Mech Engn, Beijing 100083, Peoples R China
8.CAS Ctr Excellence Brain Sci & Intelligence Techn, Shanghai 200031, Peoples R China
推荐引用方式
GB/T 7714		 Li, Yinlin,Jia, Lihao,Wang, Zidong,et al. Un-supervised and semi-supervised hand segmentation in egocentric images with noisy label learning[J]. NEUROCOMPUTING,2019,334:11-24.
APA Li, Yinlin,Jia, Lihao,Wang, Zidong,Qian, Yang,&Qiao, Hong.(2019).Un-supervised and semi-supervised hand segmentation in egocentric images with noisy label learning.NEUROCOMPUTING,334,11-24.
MLA Li, Yinlin,et al."Un-supervised and semi-supervised hand segmentation in egocentric images with noisy label learning".NEUROCOMPUTING 334(2019):11-24.

入库方式： OAI收割

来源：自动化研究所

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