Automatic association method of knowledge points about karst landform VR panoramic teaching resources

Fusheng Mei; Wencai Huang; Zheng Zhong; Ting Yan

doi:10.1117/12.2652468

6 September 2022 Automatic association method of knowledge points about karst landform VR panoramic teaching resources

Fusheng Mei, Wencai Huang, Zheng Zhong, Ting Yan

Proceedings Volume 12332, International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2022); 123320P (2022) https://doi.org/10.1117/12.2652468
Event: International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2022), 2022, Chengdu, China

Abstract

VR panoramic teaching resources can create an immersive teaching situation for teachers and students. Aiming at the problems of tedious manual annotation and easy omission of VR panoramic teaching resources during the course preparation of karst landform teaching teachers, this paper designs an automatic association method for knowledge points of VR panoramic teaching resources to construct the training set of karst landform sample images based on Convolution Neural Network(CNN), which can extract the karst landform teaching objects in the panoramic images, and associates and locates the knowledge points stored in the object relational database in the VR panoramic space. Finally, a prototype system of "Geographical Karst" teaching course of senior high school geography published by People’s Education Press is constructed. The experimental results show that this method can realize the automatic correlation of VR panoramic teaching resource knowledge points.

Citation Download Citation

Fusheng Mei, Wencai Huang, Zheng Zhong, and Ting Yan "Automatic association method of knowledge points about karst landform VR panoramic teaching resources", Proc. SPIE 12332, International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2022), 123320P (6 September 2022); https://doi.org/10.1117/12.2652468

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