<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In this paper, on the basis of the Unity3D engine, image feature points are coarsely extracted, and a quadtree-based division algorithm is applied to filter the optimal FAST corner points. The fast 3D reconstruction technique is constructed through the construction method of nonlinear scale space similar to scale-invariant feature transform (SIFT), which is layer incremented according to the scale level logarithmic layer. The reconstructed 3D virtual teaching laboratory tool is obtained by importing the matched feature points into the model after the diffusion is completed. Finally, the teaching process and teacher-student behavioral data analysis were conducted for TCM and acupuncture students using the medical aromatherapy experimental course “Clinical Experiment of Aromatherapy for Primary Dysmenorrhea” as the teaching objective. The results showed that the maximum value of iFIAS of the experimental group was 100, and the mean value was 79.35, while the maximum value of technical iFIAS of the control group was only 51.32, and the mean value was 21.34, which was a significant difference between the two. It shows that the teaching method improves classroom learning interest and effect. The purpose of this paper is to provide relevant opinions and references for the future development direction of the combination of aromatherapy teaching and 3D virtual reality.</p>
</abstract>

In this paper, on the basis of the Unity3D engine, image feature points are coarsely extracted, and a quadtree-based division algorithm is applied to filter the optimal FAST corner points. The fast 3D reconstruction technique is constructed through the construction method of nonlinear scale space similar to scale-invariant feature transform (SIFT), which is layer incremented according to the scale level logarithmic layer. The reconstructed 3D virtual teaching laboratory tool is obtained by importing the matched feature points into the model after the diffusion is completed. Finally, the teaching process and teacher-student behavioral data analysis were conducted for TCM and acupuncture students using the medical aromatherapy experimental course “Clinical Experiment of Aromatherapy for Primary Dysmenorrhea” as the teaching objective. The results showed that the maximum value of iFIAS of the experimental group was 100, and the mean value was 79.35, while the maximum value of technical iFIAS of the control group was only 51.32, and the mean value was 21.34, which was a significant difference between the two. It shows that the teaching method improves classroom learning interest and effect. The purpose of this paper is to provide relevant opinions and references for the future development direction of the combination of aromatherapy teaching and 3D virtual reality.

Construction of medical aromatherapy experimental teaching resources based on digital three-dimensional technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In this paper, on the basis of the Unity3D engine, image feature points are coarsely extracted, and a quadtree-based division algorithm is applied to filter...

Construction of medical aromatherapy experimental teaching resources based on digital three-dimensional technology

Online veröffentlicht: 05. Dez. 2023

Seitenbereich: -

Eingereicht: 18. Jan. 2023

Akzeptiert: 15. Juni 2023

DOI: https://doi.org/10.2478/amns.2023.2.01371

Schlüsselwörter
unity3D engine, Nonlinear scale space, Feature transformation, Fast 3D reconstruction, Aromatherapy

© 2023 Jing Xu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Construction of medical aromatherapy experimental teaching resources based on digital three-dimensional technology

Online veröffentlicht: 05. Dez. 2023

Seitenbereich: -

Eingereicht: 18. Jan. 2023

Akzeptiert: 15. Juni 2023

DOI: https://doi.org/10.2478/amns.2023.2.01371

Schlüsselwörterunity3D engine, Nonlinear scale space, Feature transformation, Fast 3D reconstruction, Aromatherapy

© 2023 Jing Xu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
unity3D engine, Nonlinear scale space, Feature transformation, Fast 3D reconstruction, Aromatherapy