• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.432-443
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• 2017

The primary goal of the MPEG-H 3D Audio standard is to provide immersive audio environments for high-resolution broadcasting services such as UHDTV. This standard incorporates a wide range of technologies such as encoding/decoding technology for multi-channel/object/scene-based signal, rendering technology for providing 3D audio in various playback environments, and post-processing technology. The reference software decoder of this standard is a structure combining several modules and can operate in various modes. Each module is composed of independent executable files and executed sequentially, real time decoding is impossible. In this paper, we make DLL library of the core decoder, format converter, object renderer, and binaural renderer of the standard and integrate them to enable frame-based decoding. In addition, by measuring the computation complexity of each mode of the MPEG-H 3D-Audio decoder, this paper also provides a reference for selecting the appropriate decoding mode for various hardware platforms. As a result of the computational complexity measurement, the low complexity profiles included in Korean broadcasting standard has a computation complexity of 2.8 times to 12.4 times that of the QMF synthesis operation in case of rendering as a channel signals, and it has a computation complexity of 4.1 times to 15.3 times of the QMF synthesis operation in case of rendering as a binaural signals.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.948-955
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• 2019

As interests in 360-degree VR (Virtual Reality) video services enormously grow, compression and streaming technologies for VR video data have been rapidly developed. Quality Emphasized Region (QER) based streaming scheme has been developed as a kind of viewport-adaptive 360-degree video streaming technology for maintaining immersive experience and reducing bandwidth waste. For selecting a QER corresponding to the user's gaze coordinate, QER-based streaming scheme requires the calculation of Quality Emphasis Center (QEC) distance and signaling message delivery for requesting QER switching. QEC distance calculations require high computational complexity because of repeated calculations as many times as the number of QERs. Furthermore, the signaling message interval results in a trade-off relationship between efficient bandwidth usage and flexible QER switching. In this paper, we propose an improved QER selection algorithm based on MMT protocol to solve this problem. The proposed algorithm could achieve computational complexity reduction by using preprocessed QER_ID_MAP. Also, flexible QER switching could be achieved, as well as efficient bandwidth utilization by an adaptive adjustment of the signaling interval.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.283-292
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• 2018

UHD (Ultra High Definition) broadcasting technology, and UWV (Ultra Wide Vision) which is the high quality panoramic video of wide view angle based on UHD, were commercialized in Korea for the first time in the world, and those are representative realistic video technologies that maximize the user's sense of presence. By comparing the user's subjective reaction of UHD and UWV, the purpose of this study is to systematically establish the user's subjective video quality evaluation. For this purpose, a large screen projection experiment is designed by setting the screen size (4k x 2k, 8k x 2k) and content types (sports, landscape, concert) as variables to measure the user's subjective video quality evaluation and satisfaction. As a result of the study, the users' evaluation of UWV was higher than UHD in all items of subjective video quality, and satisfaction. Moreover, the results showed the significant differences depending on the video contents. Based on the results of the research, the study proposed the points necessary for the development and commercialization of UWV panoramic technology, and suggestions for the future research.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.175-201
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• 2023

In the midst of going through a non-face-to-face society, most of human activities narrowed down to the platform, restrictions on external activities are bringing the internal scalability of digital technology. Metaverse is virtually shifting reality and increasing the possibility of utilization in various areas. However, researches linked to the educational effects of metaverse, especially students with disabilities, are still an unknown area that lacks exploration. This paper focuses on the fact that metaverse-education is widening educational fields that meets the various needs of disabled students to realize social good and inclusive education, and communication effects such as resolving barriers to interaction are prominent. As a research method, examining literature research papers linked to AR/VR, metaverse with communication skills, interviews, articles, and columns by experts, and policy suggestions and implications for the special education was conducted. Although the limitations of research are confirmed, significant results are found on inclusive education, which provides educational maximizing effects and realizing human rights through direct immersive experience reflecting the Cone of Experience Theory. Hopefully follow-up studies on meta-edu for disabled students will be carried out in the future, and various interdisciplinary discussions are needed to carefully observe inclusive policies and benefits so that the socially vulnerable are not excluded from technologies in ICT society.

• Information Systems Review
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• v.22 no.2
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• pp.25-41
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• 2020

Along with the expectation about 5G network commercialization, interests in realistic and immersive media industries such as virtual reality (VR) are increasing. However, most of studies on VR still focus on video technologies instead of factors for popularity and consumption. Thus, the main objective of this research is to identify meaningful factors, which affect the view counts of VR videos and to provide business implications of the content strategies for VR video creators and service providers. Using a regression analysis with 700 VR videos, this study tries to find major factors that affect the view counts of VR videos. As a result, user assessment factors such as number of likes and sicknesses have a strong influence on the view counts. In addition, the result shows that both general information factors (video length and age) and content characteristic factors (series, one source multi use (OSMU), and category) are all influential factors. The findings suggest that it is necessary to support recommendation and curation based on user assessments for increasing popularity and diffusion of VR video streaming.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.99-107
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• 2024

While the demand for extrapolating video content horizontally or vertically is increasing, even the most advanced techniques cannot successfully extrapolate all videos. Therefore, it is important to determine if a given video can be well extrapolated before attempting the actual extrapolation. This can help avoid wasting computing resources. This paper proposes a video classifier that can identify if a video is suitable for horizontal extrapolation. The classifier utilizes optical flow and an adaptive Gaussian blur network, which can be applied to flow-based video extrapolation methods. The labeling for training was rigorously conducted through user tests and quantitative evaluations. As a result of learning from this labeled dataset, a network was developed to determine the extrapolation capability of a given video. The proposed classifier achieved much more accurate classification performance than methods that simply use the original video or fixed blur alone by effectively capturing the characteristics of the video through optical flow and adaptive Gaussian blur network. This classifier can be utilized in various fields in conjunction with automatic video extrapolation techniques for immersive viewing experiences.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1326-1327
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• 2024

The construction industry is renowned for its dynamic and intricate characteristics, which demand proficient leadership skills for successful project management. However, the existing training platforms within this sector often overlook the significance of soft skills in leadership development. These platforms primarily focus on safety, work processes, and technical modules, leaving a noticeable gap in preparing future leaders, especially students in the construction domain, for the complex challenges they will encounter in their professional careers. It is crucial to recognize that effective leadership in construction projects requires not only technical expertise but also the ability to communicate effectively, collaborate with diverse stakeholders, and navigate complex relationships. These soft skills are critical for managing teams, resolving conflicts, and driving successful project outcomes. In addition, the construction sector has been slow in adopting and harnessing the potential of advanced emerging technologies such as virtual reality, artificial intelligence, to enhance the soft skills of future leaders. Therefore, there is a need for a platform where students can practice complex situations and conversations in a safe and repeatable training environment. To address these challenges, this study proposes a pioneering approach by integrating conversational AI techniques using large language models (LLMs) within virtual worlds. Although LLMs like ChatGPT possess extensive knowledge across various domains, their responses may lack relevance in specific contexts. Prompt engineering techniques are utilized to ensure more accurate and effective responses, tailored to the specific requirements of the targeted users. This involves designing and refining the input prompts given to the language model to guide its response generation. By carefully crafting the prompts and providing context-specific instructions, the model can generate responses that are more relevant and aligned with the desired outcomes of the training program. The proposed system offers interactive engagement to students by simulating diverse construction site roles through conversational AI based agents. Students can face realistic challenges that test and enhance their soft skills in a practical context. They can engage in conversations with AI-based avatars representing different construction site roles, such as machine operators, laborers, and site managers. These avatars are equipped with AI capabilities to respond dynamically to user interactions, allowing students to practice their communication and negotiation skills in realistic scenarios. Additionally, the introduction of AI instructors can provide guidance, feedback, and coaching tailored to the individual needs of each student, enhancing the effectiveness of the training program. The AI instructors can provide immediate feedback and guidance, helping students improve their decision-making and problem-solving abilities. The proposed immersive learning environment is expected to significantly enhance leadership competencies of students, such as communication, decision-making and conflict resolution in the practical context. This study highlights the benefits of utilizing conversational AI in educational settings to prepare construction students for real-world leadership roles. By providing hands-on, practical experience in dealing with site-specific challenges, students can develop the necessary skills and confidence to excel in their future roles.