• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.351-352
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• 2021

Due to the recent rapid change in the social environment due to Corona 19, the need for non-face-to-face/contact-based information exchange technology is rapidly emerging. Due to these changes, the development of an alternative system using a sense of immersion and a sense of presence is urgently required. In this study, in order to implement a video conferencing system, we implemented a technology for transmitting large-capacity 3D data in real time without delay. For this, the applied algorithm of GAN, the latest deep learning algorithm of the unsupervised learning series, was used.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.7
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• pp.93-99
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• 2015

In this paper, we propose a gaze correction method for realistic video teleconferencing. Typically, cameras used in teleconferencing are installed at the side of the display monitor, but not in the center of the monitor. This system makes it too difficult for users to contact each eyes. Therefore, eys contact is the most important in the immersive videoconferencing. In the proposed method, we use the stereo camera and the depth camera to correct the eye contact. The depth camera is the kinect camera, which is the relatively cheap price, and estimate the depth information efficiently. However, the kinect camera has some inherent disadvantages. Therefore, we fuse the kinect camera with stereo camera to compensate the disadvantages of the kinect camera. Consecutively, for the gaze-corrected image, view synthesis is performed by 3D warping according to the depth information. Experimental results verify that the proposed system is effective in generating natural gaze-corrected images.