Author(s)

Yanyu Liu ¹, Donghui Bao ¹, Lili Ye ², Yanyan Chen ¹

Affiliation(s)

¹ School of Electronic Information Engineering, Beihai Vocational College, Beihai, 536000, China
² Yifu Primary School of Haicheng District, Beihai City, Beihai, 536000, China

Corresponding Author

Yanyu Liu

ABSTRACT

3D education has vivid three-dimensional expression and powerful interactive functions, which is in line with the situational teaching and cognitive requirements of schoolchild. It is an excellent platform for displaying teaching content, and more importantly, it can improve schoolchildren’s learning enthusiasm. This article implements a three-dimensional curriculum teaching mode application, breaking away from the singularity of two-dimensional view teaching mode in presenting information. The educational scene is built on the WebGL framework based on Three.js, and a Web3D education platform suitable for young children is constructed to achieve three-dimensional teaching scene. At the same time, the facial expression recognition algorithm and human action recognition algorithm based on deep learning are applied to the Web3D education platform to achieve natural and real-time human-computer interaction in the teaching process without manual input instructions, so that learners can feel the sense of participation and immersion brought by intelligent interaction, and increase the fun of learning.

KEYWORDS

Education platform; Schoolchild; Facial expression recognition; Action recognition

CITE THIS PAPER

Yanyu Liu, Donghui Bao, Lili Ye, Yanyan Chen, Development of Web3D education platform suitable for schoolchild. Journal of Image Processing Theory and Applications (2023) Vol. 6: 122-131. DOI: http://dx.doi.org/10.23977/jipta.2023.060114.

REFERENCES

[1] Sujie Wu: Cross-platform Application Research on Three Dimensional Interactive Courseware (Master, hebei normal university, China 2017). 
[2] Ke Liu. Design and Application of 3D Visualization Resources in Teaching Scene (Master, Central China Normal University, China 2017).
[3] Qiang Fang. The Research and Implementation of WebGL Based 3D Graphics Engine (Master, Anhui University, China 2013).
[4] X. Kang, Q. Peng. Integration of CAD models with product assembly planning in a Web-based 3D visualized environment [J]. International Journal on Interactive Design and Manufacturing (IJIDeM), 2014, 8(2): 121-131.
[5] L. Morrish, N. Rickard, T. C. Chin, et al. Emotion regulation in adolescent well-being and positive education [J]. Journal of Happiness Studies, 2018, 19(5): 1543-1564.
[6] J. T. Cacioppo, L. G. Tassinary. Inferring psychological significance from physiological signals [J]. American psychologist, 1990, 45(1): 16. 
[7] C. Darwin, P. Prodger. The expression of the emotions in man and animals[M]. USA: Oxford University Press, 1998.
[8] I. Cohen, N. Sebe, A. Garg, et al. Facial expression recognition from video sequences: temporal and static modeling[J]. Computer Vision and image understanding, 2003, 91(1-2): 160-187.
[9] Z. Zeng, M. Pantic, G. I. Roisman, et al. A survey of affect recognition methods: Audio, visual, and spontaneous expressions [J]. IEEE transactions on pattern analysis and machine intelligence, 2008, 31(1): 39-58.
[10] C. W. Hsu, C. C. Chang, C. J. Lin. A practical guide to support vector classification[J]. BJU International, 2008, 101(1): 1396-1400. 
[11] P. Viola, M. Jones. Rapid object detection using a boosted cascade of simple features[C]. 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2001, with CD-ROM, Kauai, HI, USA, December 8-14, 2001, 511-518. 
[12] M. Osadchy, Y. L. Cun, M. L. Miller. Synergistic face detection and pose estimation with energy-based models[J]. Journal of Machine Learning Research, 2007, 8(1): 1197-1215. 
[13] P. Liu, S. Han, Z. Meng, et al. Facial expression recognition via a boosted deep belief network[C]. 2014 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014, Columbus, OH, USA, June 23-28, 2014, 1805-1812.
[14] X. Chen, X. Yang, M. Wang, et al. Convolution neural network for automatic facial expression recognition[C]. 2017 International conference on applied system innovation (ICASI), Sapporo, Japan, May 13-17, 2017, 814-817. 
[15] A. T. Lopes, D. E. Aguiar, T. Oliveira-Santos. A facial expression recognition system using convolutional networks[C]. 28th SIBGRAPI Conference on Graphics, Patterns and Images, SIBGRAPI 2015, Salvador, Bahia, Brazil, August 26-29, 2015, 273-280. 
[16] I. Choi, H. Ahn, J. Yoo. Facial expression classification using deep convolutional neural network [J]. Journal of Electrical Engineering&Technology, 2018, 13(1): 485-492
[17] Liu C, Freeman W T, Adelson E H, et al. Human-assisted motion annotation[C]. //Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on. IEEE, 2008:1-8 
[18] Akihiro I, Nobutaka S, Yoshiaki S. Computer Vision - ACCV 2007[M]. Springer Berlin Heidelberg, 2007
[19] Abd-Almageed W, Davis L. Human detection using iterative feature selection and logistic principal component analysis[C]. //Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on. IEEE
[20] Xie L, Pan W, Tang C, et a1. A pyramidal deep learning architecture for humanaction recognition [J].Journal of Modelling Identification and Control,2014, 21(2): 139.146
[21] Gaves A, Mohamed AR, Hinton G. Speech recognition with deep recurrent neural networks. 2013 IEEE International Conference on Acoustics, Speech and Signal Processing. Vancouver: IEEE, 2013. 6645–6649.

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