• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.90-97
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• 2020

Recently, with the growth of mixed reality industrial infrastructure, relevant convergence research has been proposed. For real-time mixed reality services such as remote video conferencing, the research on real-time acquisition-process-transfer methods is required. This paper aims to implement an AR remote rendering method of volumetric 3D video data. We have proposed and implemented two modules; one, the parsing module of the volumetric 3D video to a game engine, and two, the server rendering module. The result of the experiment showed that the volumetric 3D video sequence data of about 15 MB was compressed by 6-7%. The remote module was streamed at 27 fps at a 1200 by 1200 resolution. The results of this paper are expected to be applied to an AR cloud service.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.157-163
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• 2013

In this paper, we propose a vision and depth information based real-time hand gesture interface method using finger joint estimation. For this, the areas of left and right hands are segmented after mapping of the visual image and depth information image, and labeling and boundary noise removal is performed. Then, the centroid point and rotation angle of each hand area are calculated. Afterwards, a circle is expanded at following pattern from a centroid point of the hand to detect joint points and end points of the finger by obtaining the midway points of the hand boundary crossing and the hand model is recognized. Experimental results that our method enabled fingertip distinction and recognized various hand gestures fast and accurately. As a result of the experiment on various hand poses with the hidden fingers using both hands, the accuracy showed over 90% and the performance indicated over 25 fps. The proposed method can be used as a without contacts input interface in HCI control, education, and game applications.