Embedded Files
Immersive Learning Environment for STEM Education (On-going)
Immersive Learning Environment for STEM Education (On-going)
Description: Learning and teaching science, technology, engineering, and mathematics (STEM) has its own unique set of difficulties in secondary and higher education. This is in part due to the abstract nature of concepts in STEM disciplines and the wide range of issues, such as cognitive load, required spatial thinking, and the necessity for experiential and hands-on learning. Most STEM-related fields require laboratory courses that are essential for providing students with the opportunity to interact with and gain experience using scientific equipment, expensive instruments, and equipment available in science labs. Virtual Reality (VR) is a potentially suitable tool to support STEM education where users can learn about complex concepts, conducting experiments (physics, chemistry) in a safe and inexpensive 3D virtual environment. With the introduction of consumer-oriented VR devices such as Meta Quest, high-speed, low-latency access networks (e.g., 5G, satellite broadband networks), VR technology has become more affordable and accessible than ever before. The goal of this project is to develop immersive learning environments for STEM education.
Publications
Iwai Wataru, Tetsuhito Oorui, Duc Nguyen, "A Networked Virtual Reality System for Real-Time Immersive Learning", in 2024 IEEE 13th Global Conference on Consumer Electronics (GCCE), Kitakyushu, Japan, Oct. 2024, pp. 1127-1128, doi: 10.1109/GCCE62371.2024.10760577.
Wataru Iwai, Tetsuto Oorui, Duc Nguyen, "Development of a System for Conducting Classes in Virtual Reality Environment" in Proc. The 28th Annual Conference of the Virtual Reality Society of Japan, Sep. 2023, Tokyo, Japan. [pdf]
Aizawa Shuta, Sakurai Shouta, Duc Nguyen, "Design and Implementation of a Web-based Multi-user Virtual Reality System for Virtual Tour of Remote Places", Proc. The International Workshop on Immersive Mixed and Virtual Environment Systems (MMVE' 23), June 2023, Vancouver, Canada.
Duc Nguyen, Shibasaki Takara, Yaginuma Manato, "Impacts of Update Frequency to User Experience in Collaborative Virtual Environments", 18th IEEE Symposium on Broadband Multimedia Systems and Broadcasting, June 2023, Beijing, China. [pdf]
[A VR-based learning environment for biology education]
Virtual Reality-based Telepresence System for Remote Participant (On-going)
Virtual Reality-based Telepresence System for Remote Participant (On-going)
Goal: This project aims to develop a Telepresence System for Online Learning utilizing Virtual Reality. The system will allow remote users to participate in classes as if they were actually in the physical classroom. The system features recording and streaming of omnidirectional video and audio, which are then displayed to users using a Head-mounted Display for an immersive experience.
Publications
Cost-effective 360-degree video streaming over networks (On-going)
Goal: 360-degree video is an essential element in VR/AR systems. To provide an excellent immersive experience, 360-degree videos require extremely high resolution with high frame rate (4K/8K + 60/90 fps). As a result, 360 video has a much higher bandwidth compared with conventional 2D video. The goal of this project is to propose cost-effective delivery methods for bulky 360-degree videos for the wide adoption of VR/AR applications.
Related Publications
Duc Nguyen, Le Ngan, Lai Huyen Thuong, Truong Thu Huong, "LL-VAS: Adaptation Method for Low-Latency 360-Degree Video Streaming over Mobile Networks", Proc. IEEE ISCC, Jun. 2022, Greece.
Duc Nguyen, N. V. Hung, N. T. Phong, T. T. Huong and T. C. Thang, "Scalable Multicast for Live 360-degree Video Streaming over Mobile Networks", IEEE Access, vol. 10, pp. 38802-38812, Apr. 2022.
Duc V. Nguyen, Huyen T. T. Tran, Truong Cong Thang, "An Evaluation of Tile Selection Methods for Viewport Adaptive Streaming of 360-degree Video", ACM Transactions on Multimedia Computing, Communications and Applications , vol. 1, 2020.
Duc V. Nguyen, Hoang Van Trung, Hoang Le Dieu Huong, Truong Thu Huong, Pham Ngoc Nam, Truong Cong Thang, "Scalable 360 video streaming using HTTP/2", IEEE MMSP 2019.
D. V. Nguyen, Huyen T.T. Tran, Anh T. Pham, Truong Cong Thang, “An Optimal Tile-based Approach for Viewport-adaptive 360-degree Video Streaming”, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, Special Issue on Immersive Video Coding and Transmission, March. 2019.
D.V. Nguyen, Huyen T.T. Tran, Truong Cong Thang, "A client-based adaptation framework for 360-degree video streaming", Journal of Visual Communication and Image Representation, Vol. 59, Feb. 2019, pp 231-243.
Modeling and Evaluating QoE of Video Streaming (On-going)
Modeling and Evaluating QoE of Video Streaming (On-going)
Goal: This project aims to study user perception of various video content types, from traditional videos to Virtual Reality videos, and user-generated content. The main task is to identify the factors affecting the user perception of video content. Various modelling approaches are then applied to build models that can accurately predict user perception of a given content.
Related publications:
Deep Transfer Learning for Recommender System
Deep Transfer Learning for Recommender System
Goal: Recommender System is playing a key role in providing personalized experience to users of many systems such as E-commerce websites, online news/videos. Despite of significant progress over the past few years, recommender system is still facing the long-standing data sparsity problem. This problem arises due to the fact that each item (i.e., books, movies) are only purchased or rated by a few users, meanwhile the number of items are very large (hundred of thousands). This project aims to address the data sparsity problem in recommender system by means of transfer learning, which is able to transfer knowledge learned from one domain to another related domain.
Related publications:
Duc Nguyen et al., "On the Transferability of Deep Networks for Recommendation Systems" (ECMLPKDD2020 IAL2020 workshop, Sep. 2020)
Hao Niu, Duc Nguyen, "Multi-source Transfer Learning for Human Activity Recognition in Smart Homes", (IEEE SMARTCOMP, Sep. 2020)
Page updated
Google Sites
Report abuse