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STUDENT ATTENTIVENESS CLASSIFICATION USING GEOMETRIC MOMENTS AIDED POSTURE ESTIMATION

<p> Body Posture provides enough information regarding the current state of mind of a person. This idea is used to implement a system that provides feedback to lecturers on how engaging the class has been by identifying the attentive levels of students. This is carried out using the posture information extracted with the help of Mediapipe. A novel method of extracting features are from the key points returned by Mediapipe is proposed. Geometric moments aided features classification performs better than the general distances and angles features classification. In order to extend the single person pose classification to multi person pose classification object detection is implemented. Feedback is generated regarding the entire lecture and provided as the output of the system. </p>

  1. 10.25394/pgs.21644849.v1
Identiferoai:union.ndltd.org:purdue.edu/oai:figshare.com:article/21644849
Date30 November 2022
CreatorsGowri Kurthkoti Sridhara Rao (14191886)
Source SetsPurdue University
Detected LanguageEnglish
TypeText, Thesis
RightsCC BY 4.0
Relationhttps://figshare.com/articles/thesis/STUDENT_ATTENTIVENESS_CLASSIFICATION_USING_GEOMETRIC_MOMENTS_AIDED_POSTURE_ESTIMATION/21644849

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