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김동신(Dongsin Kim),오병태(Byung Tae Oh) 한국방송·미디어공학회 2021 한국방송공학회 학술발표대회 논문집 Vol.2021 No.11
In this paper, we propose a new method for improving compression efficiency of immersive video using reinforcement learning. Immersive video means a video that a user can directly experience, such as 3DOF+ videos and Point Cloud videos. It has a vast amount of information due to their characteristics. Therefore, lots of compression methods for immersive video are being studied, and generally, a method, which projects an 3D image into 2D image, is used. However, in this process, a region where information does not exist is created, and it can decrease the compression efficiency. To solve this problem, we propose the reinforcement learning-based filling method with considering the characteristics of images. Experimental results show that the performance is better than the conventional padding method.