Utilizing gaze behavior for inferring task transitions using abstract hidden Markov models
We demonstrate an improved method for utilizing observed gaze behavior and show that it is useful in inferring hand movement intent during goal directed tasks. The task dynamics and the relationship between hand and gaze behavior are learned using an Abstract Hidden Markov Model (AHMM). We show that...
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2012
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oai:animorepository.dlsu.edu.ph:faculty_research-146992024-07-29T05:40:12Z Utilizing gaze behavior for inferring task transitions using abstract hidden Markov models Pinpin, Lord Kenneth M. Gamarra, Daniel Fernando Tello Johansson, Roland S. Laschi, Cecilia Dario, Paolo We demonstrate an improved method for utilizing observed gaze behavior and show that it is useful in inferring hand movement intent during goal directed tasks. The task dynamics and the relationship between hand and gaze behavior are learned using an Abstract Hidden Markov Model (AHMM). We show that the predicted hand movement transitions occur consistently earlier in AHMM models with gaze than those models that do not include gaze observations. 2012-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/12798 Faculty Research Work Animo Repository Bionics Gaze Robots—Control systems Hidden Markov models Artificial intelligence Artificial Intelligence and Robotics |
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De La Salle University |
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De La Salle University Library |
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Asia |
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Philippines Philippines |
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De La Salle University Library |
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DLSU Institutional Repository |
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Bionics Gaze Robots—Control systems Hidden Markov models Artificial intelligence Artificial Intelligence and Robotics |
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Bionics Gaze Robots—Control systems Hidden Markov models Artificial intelligence Artificial Intelligence and Robotics Pinpin, Lord Kenneth M. Gamarra, Daniel Fernando Tello Johansson, Roland S. Laschi, Cecilia Dario, Paolo Utilizing gaze behavior for inferring task transitions using abstract hidden Markov models |
| description |
We demonstrate an improved method for utilizing observed gaze behavior and show that it is useful in inferring hand movement intent during goal directed tasks. The task dynamics and the relationship between hand and gaze behavior are learned using an Abstract Hidden Markov Model (AHMM). We show that the predicted hand movement transitions occur consistently earlier in AHMM models with gaze than those models that do not include gaze observations. |
| format |
text |
| author |
Pinpin, Lord Kenneth M. Gamarra, Daniel Fernando Tello Johansson, Roland S. Laschi, Cecilia Dario, Paolo |
| author_facet |
Pinpin, Lord Kenneth M. Gamarra, Daniel Fernando Tello Johansson, Roland S. Laschi, Cecilia Dario, Paolo |
| author_sort |
Pinpin, Lord Kenneth M. |
| title |
Utilizing gaze behavior for inferring task transitions using abstract hidden Markov models |
| title_short |
Utilizing gaze behavior for inferring task transitions using abstract hidden Markov models |
| title_full |
Utilizing gaze behavior for inferring task transitions using abstract hidden Markov models |
| title_fullStr |
Utilizing gaze behavior for inferring task transitions using abstract hidden Markov models |
| title_full_unstemmed |
Utilizing gaze behavior for inferring task transitions using abstract hidden Markov models |
| title_sort |
utilizing gaze behavior for inferring task transitions using abstract hidden markov models |
| publisher |
Animo Repository |
| publishDate |
2012 |
| url |
https://animorepository.dlsu.edu.ph/faculty_research/12798 |
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1806511033990250496 |