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A Lightweight Mobile Outdoor Augmented Reality Method Using Deep Learning and Knowledge Modeling for Scene Perception to Improve Learning Experience

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成果类型:
期刊论文
作者:
Zhao, Gang;Liu, Shan*;Zhu, Wen-Juan*;Qi, Yu-Heng
通讯作者:
Liu, Shan;Zhu, Wen-Juan
作者机构:
[Qi, Yu-Heng; Liu, Shan; Zhu, Wen-Juan; Liu, S; Zhao, Gang] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan 430079, Peoples R China.
通讯机构:
[Liu, S; Zhu, WJ] C
Cent China Normal Univ, Sch Educ Informat Technol, Wuhan 430079, Peoples R China.
语种:
英文
关键词:
Augmented reality;Learning systems;Object detection;Detection accuracy;Learning experiences;Learning motivation;Learning situation;Mobile augmented reality;Objective criteria;Outdoor augmented reality;Technology solutions;Deep learning
期刊:
International Journal of Human-Computer Interaction
ISSN:
1044-7318
年:
2021
卷:
37
期:
9
页码:
884-901
基金类别:
This work was supported by the Project named Research on Outdoor Experiential Learning Environment Construction Method Based on Scene Perception granted by the Humanities and Social Science project of Chinese Ministry of Education under Grant number 17YJA880104; and the Research on Automatic Segmentation and Recognition of Teaching Scene with the Characteristics of Teaching Behavior of National Natural Science Foundation of China under Grant number 61977034; and the Research on Key Technology of Intelligent Education Evaluation and Service Based on Blockchain Technology (CCNU20ZN004) financially supported by self-determined research funds of CCNU from the colleges’ basic research and operation of MOE. We also thank the anonymous reviewers for their valuable comments and suggestions.
机构署名:
本校为第一且通讯机构
院系归属:
教育信息技术学院
摘要:
Mobile augmented reality (AR) technology creates realistic learning situations and a strong sense of immersion, which is conducive to enhance learning experience and stimulate learning motivation. However, existing mobile outdoor augmented reality applications generally have a complicated operation process and a mismatch between learning resources and corresponding scenes, which leads to a poor learning experience. Therefore, we propose a lightweight mobile outdoor AR method that combines deep learning and knowledge modeling to perceive learning scenes with a goal to improve learning experienc...

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