Chronological states of viewer’s intentions using hidden Markov models and features of eye movement
To determine the possibility of predicting viewer’s internal states using the hidden Markov model, several features of eye movements were introduced to the model. Performance was measured using the data from a set of eye movement features recorded during recall tests which consisted of observations...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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European Alliance for Innovation (EAI)
2014-09-01
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| Series: | EAI Endorsed Transactions on Context-aware Systems and Applications |
| Subjects: | |
| Online Access: | http://eudl.eu/doi/10.4108/casa.1.1.e5 |
| _version_ | 1811281055165972480 |
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| author | Minoru Nakayama Naoya Takahashi |
| author_facet | Minoru Nakayama Naoya Takahashi |
| author_sort | Minoru Nakayama |
| collection | DOAJ |
| description | To determine the possibility of predicting viewer’s internal states using the hidden Markov model, several features of eye movements were introduced to the model. Performance was measured using the data from a set of eye movement features recorded during recall tests which consisted of observations of three levels of task difficulty. The features were the temporal appearances of fixations and saccades, and combinations of 8 viewed directions during long and short eye movements. As a result, features of long eye movements, such as saccade information, contributed to prediction accuracy. Also, this prediction accuracy was regulated by the difficulty of the task. |
| first_indexed | 2024-04-13T01:25:48Z |
| format | Article |
| id | doaj.art-aa0d93fddd7741b7bade06f99deb0ff2 |
| institution | Directory Open Access Journal |
| issn | 2409-0026 |
| language | English |
| last_indexed | 2024-04-13T01:25:48Z |
| publishDate | 2014-09-01 |
| publisher | European Alliance for Innovation (EAI) |
| record_format | Article |
| series | EAI Endorsed Transactions on Context-aware Systems and Applications |
| spelling | doaj.art-aa0d93fddd7741b7bade06f99deb0ff22022-12-22T03:08:38ZengEuropean Alliance for Innovation (EAI)EAI Endorsed Transactions on Context-aware Systems and Applications2409-00262014-09-01111610.4108/casa.1.1.e5Chronological states of viewer’s intentions using hidden Markov models and features of eye movementMinoru Nakayama0Naoya Takahashi1Human System Science, Tokyo Institute of Technology Ookayama, Meguro, Tokyo, Japan; nakayama@cradle.titech.ac.jpHuman System Science, Tokyo Institute of Technology Ookayama, Meguro, Tokyo, JapanTo determine the possibility of predicting viewer’s internal states using the hidden Markov model, several features of eye movements were introduced to the model. Performance was measured using the data from a set of eye movement features recorded during recall tests which consisted of observations of three levels of task difficulty. The features were the temporal appearances of fixations and saccades, and combinations of 8 viewed directions during long and short eye movements. As a result, features of long eye movements, such as saccade information, contributed to prediction accuracy. Also, this prediction accuracy was regulated by the difficulty of the task.http://eudl.eu/doi/10.4108/casa.1.1.e5User intentionhidden Markov modelfeatures of eye movements |
| spellingShingle | Minoru Nakayama Naoya Takahashi Chronological states of viewer’s intentions using hidden Markov models and features of eye movement EAI Endorsed Transactions on Context-aware Systems and Applications User intention hidden Markov model features of eye movements |
| title | Chronological states of viewer’s intentions using hidden Markov models and features of eye movement |
| title_full | Chronological states of viewer’s intentions using hidden Markov models and features of eye movement |
| title_fullStr | Chronological states of viewer’s intentions using hidden Markov models and features of eye movement |
| title_full_unstemmed | Chronological states of viewer’s intentions using hidden Markov models and features of eye movement |
| title_short | Chronological states of viewer’s intentions using hidden Markov models and features of eye movement |
| title_sort | chronological states of viewer s intentions using hidden markov models and features of eye movement |
| topic | User intention hidden Markov model features of eye movements |
| url | http://eudl.eu/doi/10.4108/casa.1.1.e5 |
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