Fatigue Detection Based on Biosignals and Facial Expressions - Couverture souple

Deshmukh, Manjusha ; Rane, Pooja

9786139952670: Fatigue Detection Based on Biosignals and Facial Expressions

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ISBN 10 : 6139952670 ISBN 13 : 9786139952670

Editeur : LAP LAMBERT Academic Publishing, 2018

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Inattentiveness in drivers is the major contributing factor in road crashes. Inattention can be caused by fatigue. Alertness of a person is typically characterized by various visual cues like eyelid movement, gaze movement, head movement and facial expression which can then be extracted and concluded into drowsiness level. Mental state of the driver can also be determined by the EEG signals. Thus this project focuses on simultaneously combining multiple visual and non-visual cues to yield a more robust fatigue characterization than a single input. This approach combines facial expressions like eyelid movement and yawning for fatigue detection. The facial features are detected and then the interest points are traced using Harris corner point detection. The area covered by these interest points determines the presence or absence of drowsiness. We are also using EEG signals to deduce the mental state of driver for detection of fatigue making the system more reliable. Hence the system effectively combines the various characteristics to help avoid the mishaps caused due to the presence of fatigue in the drivers.

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�diteur: LAP LAMBERT Academic Publishing
Date d'�dition: 2018
Langue: anglais
ISBN 10: 6139952670
ISBN 13: 9786139952670
Reliure: Broch�
Nombre de pages: 52
Coordonn�es du fabricant: non disponible
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Fatigue Detection Based on Biosignals and Facial Expressions

Manjusha Deshmukh

Edit� par LAP LAMBERT Academic Publishing Nov 2018, 2018

ISBN 10 : 6139952670 ISBN 13 : 9786139952670

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Inattentiveness in drivers is the major contributing factor in road crashes. Inattention can be caused by fatigue. Alertness of a person is typically characterized by various visual cues like eyelid movement, gaze movement, head movement and facial expression which can then be extracted and concluded into drowsiness level. Mental state of the driver can also be determined by the EEG signals. Thus this project focuses on simultaneously combining multiple visual and non-visual cues to yield a more robust fatigue characterization than a single input. This approach combines facial expressions like eyelid movement and yawning for fatigue detection. The facial features are detected and then the interest points are traced using Harris corner point detection. The area covered by these interest points determines the presence or absence of drowsiness. We are also using EEG signals to deduce the mental state of driver for detection of fatigue making the system more reliable. Hence the system effectively combines the various characteristics to help avoid the mishaps caused due to the presence of fatigue in the drivers. 52 pp. Englisch. N� de r�f. du vendeur 9786139952670

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Fatigue Detection Based on Biosignals and Facial Expressions

Deshmukh, Manjusha/ Rane, Pooja

Edit� par LAP LAMBERT Academic Publishing, 2018

ISBN 10 : 6139952670 ISBN 13 : 9786139952670

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Fatigue Detection Based on Biosignals and Facial Expressions

Manjusha Deshmukh|Pooja Rane

Edit� par LAP LAMBERT Academic Publishing, 2018

ISBN 10 : 6139952670 ISBN 13 : 9786139952670

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Deshmukh ManjushaDedicated, resourceful education professional with proven ability to create and monitor policies and practices that promote a safe learning environment ensures and encourages continuous improvements for students and. N� de r�f. du vendeur 260575108

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Fatigue Detection Based on Biosignals and Facial Expressions

Manjusha Deshmukh

Edit� par LAP LAMBERT Academic Publishing Nov 2018, 2018

ISBN 10 : 6139952670 ISBN 13 : 9786139952670

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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Inattentiveness in drivers is the major contributing factor in road crashes. Inattention can be caused by fatigue. Alertness of a person is typically characterized by various visual cues like eyelid movement, gaze movement, head movement and facial expression which can then be extracted and concluded into drowsiness level. Mental state of the driver can also be determined by the EEG signals. Thus this project focuses on simultaneously combining multiple visual and non-visual cues to yield a more robust fatigue characterization than a single input. This approach combines facial expressions like eyelid movement and yawning for fatigue detection. The facial features are detected and then the interest points are traced using Harris corner point detection. The area covered by these interest points determines the presence or absence of drowsiness. We are also using EEG signals to deduce the mental state of driver for detection of fatigue making the system more reliable. Hence the system effectively combines the various characteristics to help avoid the mishaps caused due to the presence of fatigue in the drivers.VDM Verlag, Dudweiler Landstra�e 99, 66123 Saarbr�cken 52 pp. Englisch. N� de r�f. du vendeur 9786139952670

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Fatigue Detection Based on Biosignals and Facial Expressions

Manjusha Deshmukh

Edit� par LAP LAMBERT Academic Publishing, 2018

ISBN 10 : 6139952670 ISBN 13 : 9786139952670

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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Inattentiveness in drivers is the major contributing factor in road crashes. Inattention can be caused by fatigue. Alertness of a person is typically characterized by various visual cues like eyelid movement, gaze movement, head movement and facial expression which can then be extracted and concluded into drowsiness level. Mental state of the driver can also be determined by the EEG signals. Thus this project focuses on simultaneously combining multiple visual and non-visual cues to yield a more robust fatigue characterization than a single input. This approach combines facial expressions like eyelid movement and yawning for fatigue detection. The facial features are detected and then the interest points are traced using Harris corner point detection. The area covered by these interest points determines the presence or absence of drowsiness. We are also using EEG signals to deduce the mental state of driver for detection of fatigue making the system more reliable. Hence the system effectively combines the various characteristics to help avoid the mishaps caused due to the presence of fatigue in the drivers. N� de r�f. du vendeur 9786139952670

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