• Journal of Digital Convergence
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• v.20 no.2
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• pp.407-413
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• 2022

This study conducted empirical analysis through user experience and questionnaire to find out whether the technical and contextual elements of the 'COVID-19 SABER' VR game produced and developed through initial research affect the improvement of the user's visual immersion. As a result first, the hypotheses regarding the resolution, viewing angle, effect, and design quality of the technical elements were accepted, but the hypotheses regarding the frame rate and the brightness of the lighting were rejected. Next, as for the hypothesis of the contextual elements, the hypothesis about background, directing, color and texture, interest and fun was adopted, and the hypothesis about storytelling was rejected. In summary, it was concluded that in order to increase the visual immersion of VR games, technical elements resolution, viewing angle, effect, design quality, contextual elements background, directing, color and texture, interest and fun must be designed and produced. The results of this study are expected to serve as basic data for the production and development of VR games that can induce and improve user's visual immersion in the future.

• Journal of Digital Contents Society
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• v.15 no.3
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• pp.425-432
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• 2014

4K high speed camera shooting enables shooting of fast subjects in Full HD 4 times resolution without motion blur due to increase in resolution and shutter speed. However, this shooting incurs several limitations including focus, intensity of radiation and increase in data quantity. As lack of intensity of radiation may occur due to increased shutter speed, it is shoot by opening aperture and limitation in focusing follows. In addition, there is limitation in shooting records since it has restriction in storage due to increased resolution and frame rate. In this regard, this study aims to analyze the limitations shown above through production case of 4K high speed camera (Phantom Flex 4K) and to design effective workflow to overcome this.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1776-1785
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• 2015

Content Centric Network (CCN) has been introduced as a new paradigm due to a shift of users's perspective of using Internet from host-centric to content-centric. On the other hand, a demand for video streaming has been increasing. Thus, Adaptive streaming has been introduced and researched for achieving higher user's satisfaction. If an architecture of Internet is replaced with CCN architecture, it is necessary to consider adaptive video streaming in CCN according to the demand of users. However, if the same rate decision algorithm used in Internet is deployed in CCN, there are a limitation of utilizing content store (CS) in CCN router and a problem of reflecting dynamic requirements. Therefore, this paper presents a framework adequate to CCN protocol and cache utilization, adapting content naming method of exploiting regular expression to the rate decision algorithm of the existing adaptive streaming. In addition, it also improves the quality of video streaming and verifies the performance through dynamic expression strategies and selection algorithm of the strategies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.825-840
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• 2015

Adaptive bitrate (ABR) streaming technology has become an important and prevalent feature in many multimedia delivery systems, with content providers such as Netflix and Amazon using ABR streaming to increase bandwidth efficiency and provide the maximum user experience when channel conditions are not ideal. Where such systems could see improvement is in the delivery of live video with a closed loop cognitive control of video encoding. In this paper, we present streaming camera system which provides spatially and temporally adaptive video streams, learning the user's preferences in order to make intelligent scaling decisions. The system employs a hardware based H.264/AVC encoder for video compression. The encoding parameters can be configured by the user or by the cognitive system on behalf of the user when the bandwidth changes. A cognitive video client developed in this study learns the user's preferences(i.e. video size over frame rate) over time and intelligently adapts encoding parameters when the channel conditions change. It has been demonstrated that the cognitive decision system developed has the ability to control video bandwidth by altering the spatial and temporal resolution, as well as the ability to make scaling decisions.