{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T16:25:37Z","timestamp":1774628737980,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":30,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,6,8]],"date-time":"2020-06-08T00:00:00Z","timestamp":1591574400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,6,10]]},"DOI":"10.1145\/3386290.3396933","type":"proceedings-article","created":{"date-parts":[[2020,5,30]],"date-time":"2020-05-30T04:25:03Z","timestamp":1590812703000},"page":"27-33","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":45,"title":["Low-latency cloud-based volumetric video streaming using head motion prediction"],"prefix":"10.1145","author":[{"given":"Serhan","family":"G\u00fcl","sequence":"first","affiliation":[{"name":"Fraunhofer HHI, Berlin, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dimitri","family":"Podborski","sequence":"additional","affiliation":[{"name":"Fraunhofer HHI, Berlin, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas","family":"Buchholz","sequence":"additional","affiliation":[{"name":"Deutsche Telekom AG, Berlin, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas","family":"Schierl","sequence":"additional","affiliation":[{"name":"Fraunhofer HHI, Berlin, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cornelius","family":"Hellge","sequence":"additional","affiliation":[{"name":"Fraunhofer HHI, Berlin, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,6,8]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1177\/154193120304702001"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/60.2.255"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/vr.2001.913793"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/lra.2018.2864359"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinph.2010.07.010"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/bigdata.2016.7840720"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/sahcn.2017.7964928"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/tbme.2005.848378"},{"key":"e_1_3_2_1_9_1","volume-title":"https:\/\/trac.ffmpeg.org\/wiki\/Encode\/H.264. Online","author":"Guide Video Encoding","year":"2020","unstructured":"FFmpeg. 2019. H.264 Video Encoding Guide . https:\/\/trac.ffmpeg.org\/wiki\/Encode\/H.264. Online ; accessed: 2020 -03-26. FFmpeg. 2019. H.264 Video Encoding Guide. https:\/\/trac.ffmpeg.org\/wiki\/Encode\/H.264. Online; accessed: 2020-03-26."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.17487\/rfc7478"},{"key":"e_1_3_2_1_11_1","unstructured":"Rob J Hyndman and George Athanasopoulos. 2018. Forecasting: principles and practice. OTexts.  Rob J Hyndman and George Athanasopoulos. 2018. Forecasting: principles and practice. OTexts."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/tnsre.2014.2331686"},{"key":"e_1_3_2_1_13_1","volume-title":"Filed","author":"LaValle Steve","year":"2015","unstructured":"Steve LaValle and Peter Giokaris . 2015 . Perception based predictive tracking for head mounted displays. US Patent No. 9348410B2 , Filed May 22, 2014, Issued Jun. 6., 2015. Steve LaValle and Peter Giokaris. 2015. Perception based predictive tracking for head mounted displays. US Patent No. 9348410B2, Filed May 22, 2014, Issued Jun. 6., 2015."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/tvcg.2016.2518038"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097895.3097901"},{"key":"e_1_3_2_1_16_1","volume-title":"NVIDIA CloudXR Delivers Low-Latency AR\/VR Streaming Over 5G Networks to Any Device. https:\/\/blogs.nvidia.com\/blog\/2019\/10\/22\/nvidia-cloudxr. Online","author":"NVIDIA.","year":"2020","unstructured":"NVIDIA. 2019. NVIDIA CloudXR Delivers Low-Latency AR\/VR Streaming Over 5G Networks to Any Device. https:\/\/blogs.nvidia.com\/blog\/2019\/10\/22\/nvidia-cloudxr. Online ; accessed: 2020 -03-26. NVIDIA. 2019. NVIDIA CloudXR Delivers Low-Latency AR\/VR Streaming Over 5G Networks to Any Device. https:\/\/blogs.nvidia.com\/blog\/2019\/10\/22\/nvidia-cloudxr. Online; accessed: 2020-03-26."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/ism46123.2019.00017"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3301293.3302358"},{"key":"e_1_3_2_1_19_1","unstructured":"James Robinson and Cameron McCormack. 2015. Timing control for script-based animations. W3C Working Draft. https:\/\/www.w3.org\/TR\/2015\/NOTE-animation-timing-20150922  James Robinson and Cameron McCormack. 2015. Timing control for script-based animations. W3C Working Draft. https:\/\/www.w3.org\/TR\/2015\/NOTE-animation-timing-20150922"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/jetcas.2019.2899516"},{"key":"e_1_3_2_1_21_1","volume-title":"2019 IBC conference. IBC.","author":"Schreer O","year":"2019","unstructured":"O Schreer , I Feldmann , P Kauff , P Eisert , D Tatzelt , C Hellge , K M\u00fcller , T Ebner , and S Bliedung . 2019 . Lessons learnt during one year of commercial volumetric video production . In 2019 IBC conference. IBC. O Schreer, I Feldmann, P Kauff, P Eisert, D Tatzelt, C Hellge, K M\u00fcller, T Ebner, and S Bliedung. 2019. Lessons learnt during one year of commercial volumetric video production. In 2019 IBC conference. IBC."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/dcc.2016.91"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.25080\/Majora-92bf1922-011"},{"key":"e_1_3_2_1_24_1","unstructured":"Andrew Segall Vittorio Baroncini Jill Boyce Jianle Chen and Teruhiko Suzuki. 2017. Joint call for proposals on video compression with capability beyond HEVC. In JVET-H1002.  Andrew Segall Vittorio Baroncini Jill Boyce Jianle Chen and Teruhiko Suzuki. 2017. Joint call for proposals on video compression with capability beyond HEVC. In JVET-H1002."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3304109.3306217"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/2719921"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/325165.325242"},{"key":"e_1_3_2_1_28_1","volume-title":"Using Netflix machine learning to analyze Twitch stream picture quality. https:\/\/streamquality.report\/docs\/report.html. Online","year":"2020","unstructured":"Twitch. 2018. Using Netflix machine learning to analyze Twitch stream picture quality. https:\/\/streamquality.report\/docs\/report.html. Online ; accessed: 2020 -03-26. Twitch. 2018. Using Netflix machine learning to analyze Twitch stream picture quality. https:\/\/streamquality.report\/docs\/report.html. Online; accessed: 2020-03-26."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3350917"},{"key":"e_1_3_2_1_30_1","volume-title":"Motion-to-photon latency in mobile AR and VR. https:\/\/daqri.com\/blog\/motion-to-photon-latency. Online","author":"Wagner Daniel","year":"2020","unstructured":"Daniel Wagner . 2018. Motion-to-photon latency in mobile AR and VR. https:\/\/daqri.com\/blog\/motion-to-photon-latency. Online ; accessed: 2020 -03-26. Daniel Wagner. 2018. Motion-to-photon latency in mobile AR and VR. https:\/\/daqri.com\/blog\/motion-to-photon-latency. Online; accessed: 2020-03-26."}],"event":{"name":"MMSys '20: 11th ACM Multimedia Systems Conference","location":"Istanbul Turkey","acronym":"MMSys '20","sponsor":["SIGMM ACM Special Interest Group on Multimedia","SIGCOMM ACM Special Interest Group on Data Communication","SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing"]},"container-title":["Proceedings of the 30th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3386290.3396933","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3386290.3396933","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:38:26Z","timestamp":1750199906000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3386290.3396933"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,8]]},"references-count":30,"alternative-id":["10.1145\/3386290.3396933","10.1145\/3386290"],"URL":"https:\/\/doi.org\/10.1145\/3386290.3396933","relation":{},"subject":[],"published":{"date-parts":[[2020,6,8]]},"assertion":[{"value":"2020-06-08","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}