TY - GEN
T1 - A Student Action Recognition Algorithm Based on Adjusted Variational Auto Encoder
AU - Li, Simin
AU - Dai, Yaping
AU - Ji, Ye
AU - Hirota, Kaoru
AU - Dai, Wei
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Student action recognition plays an important role in detecting students learning behaivor in online courses. In order to improve the accuracy of student action recognition in classroom, an algorithm based on Adjusted Variational Auto Encoder (AVAE) is proposed. By adjusting the traditional Variational Auto Encoder (VAE) method, the proposed algorithm can effectively extract the characteristic parameters of students from classroom video images, and then recognize the students' action. Experiments show that the proposed algorithm for student action recognition preforms better than traditional VAE algorithms with higher accuracy and convergence speed, and improves the recognition accuracy by 5.13% compared with traditional Convolutional Neural Network (CNN) method.
AB - Student action recognition plays an important role in detecting students learning behaivor in online courses. In order to improve the accuracy of student action recognition in classroom, an algorithm based on Adjusted Variational Auto Encoder (AVAE) is proposed. By adjusting the traditional Variational Auto Encoder (VAE) method, the proposed algorithm can effectively extract the characteristic parameters of students from classroom video images, and then recognize the students' action. Experiments show that the proposed algorithm for student action recognition preforms better than traditional VAE algorithms with higher accuracy and convergence speed, and improves the recognition accuracy by 5.13% compared with traditional Convolutional Neural Network (CNN) method.
KW - Auto Encoder (AE)
KW - Student Action Recognition
KW - Variational Auto Encoder (VAE)
UR - http://www.scopus.com/inward/record.url?scp=85125190288&partnerID=8YFLogxK
U2 - 10.1109/CCDC52312.2021.9601627
DO - 10.1109/CCDC52312.2021.9601627
M3 - Conference contribution
AN - SCOPUS:85125190288
T3 - Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021
SP - 2750
EP - 2755
BT - Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 33rd Chinese Control and Decision Conference, CCDC 2021
Y2 - 22 May 2021 through 24 May 2021
ER -