{"title":"SAD360:球面视口感知动态平铺360度视频流","authors":"Zhijun Li, Yumei Wang, Yu Liu","doi":"10.1109/VCIP56404.2022.10008862","DOIUrl":null,"url":null,"abstract":"As a kind of medium that provides strongly immersive experience, 360° videos suffer greatly from pixel inefficiency as the content will not be fully viewed by users, leading to a high-bandwidth requirement of streaming. Recently, Tile-based streaming systems have become popular to lower bandwidth usage. However, most of these systems inevitably treat non-viewport areas as viewport because the fixed tiling configuration fails to adapt to the viewport effectively. A finer-grained tiling configuration helps adapt to the viewport, but also introduces significant encoding overhead. Recently proposed dynamic tiling systems address the issue by tiling chunks dynamically based on the features of projected 360° videos. However, because projection inherently introduces serious distortion to image, the results can be misleading. To overcome the viewport adaption problem, we propose Spherical Viewport-Aware Dynamic Tiling for 360° Video Streaming (SAD360). Given that popularity of different areas can be reflected by viewers' behaviours on the whole, a dynamic tiling algorithm is proposed to find the optimal tiling configuration for each chunk by analysing head movement data in hand on a sphere. The algorithm tries its best to generate bigger tiles to reduce encoding overhead and still manages to adapt to the viewport effectively. We also use Reinforcement Learning (RL) to solve the problem of bitrate allocation of tiles varying in size. Experiments demonstrate that our system can get a 14% average QoE gain compared with fixed tiling configuration.","PeriodicalId":269379,"journal":{"name":"2022 IEEE International Conference on Visual Communications and Image Processing (VCIP)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"SAD360: Spherical Viewport-Aware Dynamic Tiling for 360-Degree Video Streaming\",\"authors\":\"Zhijun Li, Yumei Wang, Yu Liu\",\"doi\":\"10.1109/VCIP56404.2022.10008862\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As a kind of medium that provides strongly immersive experience, 360° videos suffer greatly from pixel inefficiency as the content will not be fully viewed by users, leading to a high-bandwidth requirement of streaming. Recently, Tile-based streaming systems have become popular to lower bandwidth usage. However, most of these systems inevitably treat non-viewport areas as viewport because the fixed tiling configuration fails to adapt to the viewport effectively. A finer-grained tiling configuration helps adapt to the viewport, but also introduces significant encoding overhead. Recently proposed dynamic tiling systems address the issue by tiling chunks dynamically based on the features of projected 360° videos. However, because projection inherently introduces serious distortion to image, the results can be misleading. To overcome the viewport adaption problem, we propose Spherical Viewport-Aware Dynamic Tiling for 360° Video Streaming (SAD360). Given that popularity of different areas can be reflected by viewers' behaviours on the whole, a dynamic tiling algorithm is proposed to find the optimal tiling configuration for each chunk by analysing head movement data in hand on a sphere. The algorithm tries its best to generate bigger tiles to reduce encoding overhead and still manages to adapt to the viewport effectively. We also use Reinforcement Learning (RL) to solve the problem of bitrate allocation of tiles varying in size. Experiments demonstrate that our system can get a 14% average QoE gain compared with fixed tiling configuration.\",\"PeriodicalId\":269379,\"journal\":{\"name\":\"2022 IEEE International Conference on Visual Communications and Image Processing (VCIP)\",\"volume\":\"95 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Conference on Visual Communications and Image Processing (VCIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VCIP56404.2022.10008862\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Visual Communications and Image Processing (VCIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VCIP56404.2022.10008862","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
SAD360: Spherical Viewport-Aware Dynamic Tiling for 360-Degree Video Streaming
As a kind of medium that provides strongly immersive experience, 360° videos suffer greatly from pixel inefficiency as the content will not be fully viewed by users, leading to a high-bandwidth requirement of streaming. Recently, Tile-based streaming systems have become popular to lower bandwidth usage. However, most of these systems inevitably treat non-viewport areas as viewport because the fixed tiling configuration fails to adapt to the viewport effectively. A finer-grained tiling configuration helps adapt to the viewport, but also introduces significant encoding overhead. Recently proposed dynamic tiling systems address the issue by tiling chunks dynamically based on the features of projected 360° videos. However, because projection inherently introduces serious distortion to image, the results can be misleading. To overcome the viewport adaption problem, we propose Spherical Viewport-Aware Dynamic Tiling for 360° Video Streaming (SAD360). Given that popularity of different areas can be reflected by viewers' behaviours on the whole, a dynamic tiling algorithm is proposed to find the optimal tiling configuration for each chunk by analysing head movement data in hand on a sphere. The algorithm tries its best to generate bigger tiles to reduce encoding overhead and still manages to adapt to the viewport effectively. We also use Reinforcement Learning (RL) to solve the problem of bitrate allocation of tiles varying in size. Experiments demonstrate that our system can get a 14% average QoE gain compared with fixed tiling configuration.