Lovro Boban, Lorenzo Catania, D. Allegra, M. Sužnjević
{"title":"研究了不利网络条件下兴趣区编码对FPV无人机飞行QoE的影响","authors":"Lovro Boban, Lorenzo Catania, D. Allegra, M. Sužnjević","doi":"10.1109/ConTEL58387.2023.10198961","DOIUrl":null,"url":null,"abstract":"In this paper we evaluate an approach for increasing Quality of Experience for drone pilots. We look at the use case in which the drone is controlled in first-person view over an IP based network such as 5G. In case of congestion, the video sent by the drone needs to be encoded at a lower bitrate so as to avoid severe video artefacts and Quality of Experience degradation. We evaluate methods of how to maximize Quality of Experience for the drone pilots in degraded network conditions with low bandwidth. We evaluate the impact of Region of Interest coding and greyscale coding on subjective metrics of video quality. The testing is performed through a drone driving simulator and using commercial first-person view googles. Our findings, based on a sample size of (n = 24), indicate that ROI and greyscale coding have, in almost all cases, either no impact or a negative impact on perceived video quality of a drone pilot.","PeriodicalId":311611,"journal":{"name":"2023 17th International Conference on Telecommunications (ConTEL)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Investigating the effect of Region of Interest coding on the QoE of FPV drone piloting under adverse network conditions\",\"authors\":\"Lovro Boban, Lorenzo Catania, D. Allegra, M. Sužnjević\",\"doi\":\"10.1109/ConTEL58387.2023.10198961\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we evaluate an approach for increasing Quality of Experience for drone pilots. We look at the use case in which the drone is controlled in first-person view over an IP based network such as 5G. In case of congestion, the video sent by the drone needs to be encoded at a lower bitrate so as to avoid severe video artefacts and Quality of Experience degradation. We evaluate methods of how to maximize Quality of Experience for the drone pilots in degraded network conditions with low bandwidth. We evaluate the impact of Region of Interest coding and greyscale coding on subjective metrics of video quality. The testing is performed through a drone driving simulator and using commercial first-person view googles. Our findings, based on a sample size of (n = 24), indicate that ROI and greyscale coding have, in almost all cases, either no impact or a negative impact on perceived video quality of a drone pilot.\",\"PeriodicalId\":311611,\"journal\":{\"name\":\"2023 17th International Conference on Telecommunications (ConTEL)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 17th International Conference on Telecommunications (ConTEL)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ConTEL58387.2023.10198961\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 17th International Conference on Telecommunications (ConTEL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ConTEL58387.2023.10198961","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Investigating the effect of Region of Interest coding on the QoE of FPV drone piloting under adverse network conditions
In this paper we evaluate an approach for increasing Quality of Experience for drone pilots. We look at the use case in which the drone is controlled in first-person view over an IP based network such as 5G. In case of congestion, the video sent by the drone needs to be encoded at a lower bitrate so as to avoid severe video artefacts and Quality of Experience degradation. We evaluate methods of how to maximize Quality of Experience for the drone pilots in degraded network conditions with low bandwidth. We evaluate the impact of Region of Interest coding and greyscale coding on subjective metrics of video quality. The testing is performed through a drone driving simulator and using commercial first-person view googles. Our findings, based on a sample size of (n = 24), indicate that ROI and greyscale coding have, in almost all cases, either no impact or a negative impact on perceived video quality of a drone pilot.