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Improvement of Student Weariness Emotion in English Classroom Based on Intelligent Internet of Things and Big Data Technology
In order to improve the recognition effect of student weariness emotion in English classroom, this paper combines intelligent Internet of Things technology and big data technology to construct an improvement model of student weariness emotion in English classroom. In the process of student facial ex...
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Published in: | Occupational therapy international 2022, Vol.2022, p.1-11 |
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description | In order to improve the recognition effect of student weariness emotion in English classroom, this paper combines intelligent Internet of Things technology and big data technology to construct an improvement model of student weariness emotion in English classroom. In the process of student facial expression recognition, according to the given grayscale threshold, this paper extracts the surface contour information from the three-dimensional volume data, extracts the student’s surface contour information, and uses triangular facets to fit to form a triangular mesh. Moreover, this paper renders a triangular mesh model and shows how to speed up the calculation of PFH. In addition, this paper proposes a Fast Point Feature Histogram, which uses an iterative closest point fine registration algorithm for image registration. Finally, this paper constructs an emotion recognition model of students’ weariness in English classroom. From the test results, it can be seen that the student weariness emotion recognition system in English classroom proposed in this paper can effectively identify students’ weariness emotion. |
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In the process of student facial expression recognition, according to the given grayscale threshold, this paper extracts the surface contour information from the three-dimensional volume data, extracts the student’s surface contour information, and uses triangular facets to fit to form a triangular mesh. Moreover, this paper renders a triangular mesh model and shows how to speed up the calculation of PFH. In addition, this paper proposes a Fast Point Feature Histogram, which uses an iterative closest point fine registration algorithm for image registration. Finally, this paper constructs an emotion recognition model of students’ weariness in English classroom. 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In the process of student facial expression recognition, according to the given grayscale threshold, this paper extracts the surface contour information from the three-dimensional volume data, extracts the student’s surface contour information, and uses triangular facets to fit to form a triangular mesh. Moreover, this paper renders a triangular mesh model and shows how to speed up the calculation of PFH. In addition, this paper proposes a Fast Point Feature Histogram, which uses an iterative closest point fine registration algorithm for image registration. Finally, this paper constructs an emotion recognition model of students’ weariness in English classroom. From the test results, it can be seen that the student weariness emotion recognition system in English classroom proposed in this paper can effectively identify students’ weariness emotion.</abstract><cop>London</cop><pub>Hindawi</pub><pmid>36105071</pmid><doi>10.1155/2022/9369389</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0001-9897-840X</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Academic achievement Acknowledgment Algorithms Bias Big Data Child development Children & youth Classrooms Cognition & reasoning College students Core curriculum Education Educational technology Emotion recognition Employment Families & family life Homework Intelligence Internet Internet of Things Learning Mental health Parents & parenting Self evaluation Students Teaching methods Technology |
title | Improvement of Student Weariness Emotion in English Classroom Based on Intelligent Internet of Things and Big Data Technology |
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