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Real-time face view correction for front-facing cameras
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作者 Yudong Guo Juyong Zhang +3 位作者 Yihua Chen Hongrui Cai Zhangjin Huang Bailin Deng 《Computational Visual Media》 EI CSCD 2021年第4期437-452,共16页
Face views are particularly important in person-to-person communication.Differenes between the camera location and the face orientation can result in undesirable facial appearances of the participants during video con... Face views are particularly important in person-to-person communication.Differenes between the camera location and the face orientation can result in undesirable facial appearances of the participants during video conferencing.This phenomenon is particularly noticeable when using devices where the frontfacing camera is placed in unconventional locations such as below the display or within the keyboard.In this paper,we take a video stream from a single RGB camera as input,and generate a video stream that emulates the view from a virtual camera at a designated location.The most challenging issue in this problem is that the corrected view often needs out-of-plane head rotations.To address this challenge,we reconstruct the 3D face shape and re-render it into synthesized frames according to the virtual camera location.To output the corrected video stream with natural appearance in real time,we propose several novel techniques including accurate eyebrow reconstruction,high-quality blending between the corrected face image and background,and template-based 3D reconstruction of glasses.Our system works well for different lighting conditions and skin tones,and can handle users wearing glasses.Extensive experiments and user studies demonstrate that our method provides high-quality results. 展开更多
关键词 face view correction 3D face reconstruction deep learning online communication
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