Intelligent Recognition of Train Driver Behavior Based on Human Skeleton Information

A human poseture capture and prediction alcognition was proposed, which was used to identify violated driver. Firstly, driver behavior or action captured by camera was split into a set of successive frames with human poseture. Then each poseture in a frame was recognized by deep learning network and...

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Main Authors: Zhiyi WANG, Xinwu LIU
Format: Article
Language:zho
Published: Editorial Department of Electric Drive for Locomotives 2020-07-01
Series:机车电传动
Subjects:
Online Access:http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128x.2020.04.018
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author Zhiyi WANG
Xinwu LIU
author_facet Zhiyi WANG
Xinwu LIU
author_sort Zhiyi WANG
collection DOAJ
description A human poseture capture and prediction alcognition was proposed, which was used to identify violated driver. Firstly, driver behavior or action captured by camera was split into a set of successive frames with human poseture. Then each poseture in a frame was recognized by deep learning network and a type of behaviors composed by a set of poseture was classified via logistic regression model. Finally, the association between detected driver behaviors and locomotive LKJ data was applied in the recognition of violated driver. Compared with the daily random-check approach by inspectors in locomotive depots, this way was more reasonable and efficient. However, the accuracy of it was limited by the resolution of surveillance cameras in the driving cab of locomotive.
format Article
id doaj-art-333827ea08204bcb94bc982df168fec8
institution OA Journals
issn 1000-128X
language zho
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publisher Editorial Department of Electric Drive for Locomotives
record_format Article
series 机车电传动
spelling doaj-art-333827ea08204bcb94bc982df168fec82025-08-20T02:16:19ZzhoEditorial Department of Electric Drive for Locomotives机车电传动1000-128X2020-07-01909320922106Intelligent Recognition of Train Driver Behavior Based on Human Skeleton InformationZhiyi WANGXinwu LIUA human poseture capture and prediction alcognition was proposed, which was used to identify violated driver. Firstly, driver behavior or action captured by camera was split into a set of successive frames with human poseture. Then each poseture in a frame was recognized by deep learning network and a type of behaviors composed by a set of poseture was classified via logistic regression model. Finally, the association between detected driver behaviors and locomotive LKJ data was applied in the recognition of violated driver. Compared with the daily random-check approach by inspectors in locomotive depots, this way was more reasonable and efficient. However, the accuracy of it was limited by the resolution of surveillance cameras in the driving cab of locomotive.http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128x.2020.04.018human skeletondeep learningposeture recognitionLKJtrain
spellingShingle Zhiyi WANG
Xinwu LIU
Intelligent Recognition of Train Driver Behavior Based on Human Skeleton Information
机车电传动
human skeleton
deep learning
poseture recognition
LKJ
train
title Intelligent Recognition of Train Driver Behavior Based on Human Skeleton Information
title_full Intelligent Recognition of Train Driver Behavior Based on Human Skeleton Information
title_fullStr Intelligent Recognition of Train Driver Behavior Based on Human Skeleton Information
title_full_unstemmed Intelligent Recognition of Train Driver Behavior Based on Human Skeleton Information
title_short Intelligent Recognition of Train Driver Behavior Based on Human Skeleton Information
title_sort intelligent recognition of train driver behavior based on human skeleton information
topic human skeleton
deep learning
poseture recognition
LKJ
train
url http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128x.2020.04.018
work_keys_str_mv AT zhiyiwang intelligentrecognitionoftraindriverbehaviorbasedonhumanskeletoninformation
AT xinwuliu intelligentrecognitionoftraindriverbehaviorbasedonhumanskeletoninformation