Immersive video streaming has become very popular. To increase the quality of experience (QoE) with immersive media, user movement adaptive video streaming, three degrees of freedom plus (3DoF+), has emerged and is expected to meet this growing demand. Satisfying the limit of the bandwidth, providing high-quality immersive experience is challenging because 3DoF+ system requires high resolution, multi-view video transmission. This paper proposes a stride based 3DoF+ 360 video streaming system and introduces two main ideas: (i) a multi-view video redundancy removal method using view synthesis, (ii) a multi-view video residual packing method. The proposed multi-view video compression method removes redundancy between videos and packs them into one video, and it exhibits a BD-rate saving of 36.0% in maximum compared to the results of the high-efficiency video coding reference model. In addition, the proposed system requires fewer number of decoders for the clients, and it decreases the burden for immersive video streaming.
The moving picture experts group (MPEG) video coding group started an immersive video coding standard project to accomplish acceptable bandwidth and decoding resources for multiple immersive videos with texture (color) and geometry (depth) information. The MPEG immersive video (MIV) coding standard provides functionality to remove inter-view redundancy and merge the residuals into videos defined as atlases. Although MIV reduces the number of videos to decode, an efficient decoder instance reduction method has not been investigated. This study proposes a frame packing implementation in MIV software. The proposed method conducts frame packing for geometry atlases to align with texture atlases, encodes them as subpicture bitstreams, and merges one texture / geometry atlas into a single bitstream with a bitstream merger. Furthermore, the proposed method provides control over the number of decoder instances without significantly increasing the computational complexity compared to existing frame packing methods. Therefore, the proposed method was accepted in MIV and will be implemented on the recent version of the reference software of MIV.
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