Mood recognition using combined algorithms and methods (MR CAM)

This paper explores the study of mood recognition in order to aid in activities that concern human-computer interaction. This study is relevant to empathic computing as it should be capable of continuously recognize the emotion and automatically recognize the mood of its users. A lot of existing emo...

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Main Authors: Asedillo, Emmanuel Bryan B., Ching, Marc Lawrence, Ribas, Raphael LL., Veto, Ian Leslie S.
Format: text
Language:English
Published: Animo Repository 2010
Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/10670
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Institution: De La Salle University
Language: English
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spelling oai:animorepository.dlsu.edu.ph:etd_bachelors-113152021-10-11T13:50:23Z Mood recognition using combined algorithms and methods (MR CAM) Asedillo, Emmanuel Bryan B. Ching, Marc Lawrence Ribas, Raphael LL. Veto, Ian Leslie S. This paper explores the study of mood recognition in order to aid in activities that concern human-computer interaction. This study is relevant to empathic computing as it should be capable of continuously recognize the emotion and automatically recognize the mood of its users. A lot of existing emotion recognition techniques has been developed to solve the problem of human-computer interaction, however, these emotions only show the feeling of a user in a given instant and not that of the whole time the user has been using the system. This research aims to explore and contribute to this field of study by recognizing the emotion and mood through the use of facial expressions. This research focuses on studying existing techniques on emotion recognition from facial expressions with the use of active shape models. The people exhibit specific emotions in frontal position so as to maximize the observation of facial expressions. Features generated are formed in the 2-D model are then utilized for emotion classification techniques such as naive bayees and sequential minimal optimization. The results of the emotion classifiers play a major role in finding the mood of the person in the video as these results are the factors being considered for the mood recognition algorithm applied in the research. 2010-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/10670 Bachelor's Theses English Animo Repository
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
description This paper explores the study of mood recognition in order to aid in activities that concern human-computer interaction. This study is relevant to empathic computing as it should be capable of continuously recognize the emotion and automatically recognize the mood of its users. A lot of existing emotion recognition techniques has been developed to solve the problem of human-computer interaction, however, these emotions only show the feeling of a user in a given instant and not that of the whole time the user has been using the system. This research aims to explore and contribute to this field of study by recognizing the emotion and mood through the use of facial expressions. This research focuses on studying existing techniques on emotion recognition from facial expressions with the use of active shape models. The people exhibit specific emotions in frontal position so as to maximize the observation of facial expressions. Features generated are formed in the 2-D model are then utilized for emotion classification techniques such as naive bayees and sequential minimal optimization. The results of the emotion classifiers play a major role in finding the mood of the person in the video as these results are the factors being considered for the mood recognition algorithm applied in the research.
format text
author Asedillo, Emmanuel Bryan B.
Ching, Marc Lawrence
Ribas, Raphael LL.
Veto, Ian Leslie S.
spellingShingle Asedillo, Emmanuel Bryan B.
Ching, Marc Lawrence
Ribas, Raphael LL.
Veto, Ian Leslie S.
Mood recognition using combined algorithms and methods (MR CAM)
author_facet Asedillo, Emmanuel Bryan B.
Ching, Marc Lawrence
Ribas, Raphael LL.
Veto, Ian Leslie S.
author_sort Asedillo, Emmanuel Bryan B.
title Mood recognition using combined algorithms and methods (MR CAM)
title_short Mood recognition using combined algorithms and methods (MR CAM)
title_full Mood recognition using combined algorithms and methods (MR CAM)
title_fullStr Mood recognition using combined algorithms and methods (MR CAM)
title_full_unstemmed Mood recognition using combined algorithms and methods (MR CAM)
title_sort mood recognition using combined algorithms and methods (mr cam)
publisher Animo Repository
publishDate 2010
url https://animorepository.dlsu.edu.ph/etd_bachelors/10670
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