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This adaptive bitrate ladder enables the client\u2019s video player to dynamically adjust the quality of the video stream in real-time based on fluctuations in network conditions, ensuring uninterrupted playback by selecting the most suitable representation for the available bandwidth. The most straightforward approach involves using a fixed bitrate ladder for all videos, consisting of pre-determined bitrate-resolution pairs known as\n            <jats:italic toggle=\"yes\">one-size-fits-all<\/jats:italic>\n            . Conversely, the most reliable technique relies on intensively encoding all resolutions over a wide range of bitrates to build the\n            <jats:italic toggle=\"yes\">convex hull<\/jats:italic>\n            , thereby optimizing the bitrate ladder by selecting the representations from the convex hull for each specific video. Several techniques have been proposed to predict content-based ladders without performing a costly, exhaustive search encoding. This article provides a comprehensive review of various convex hull prediction methods, including both conventional and learning-based approaches. Furthermore, we conduct a benchmark study of several handcrafted- and deep learning (DL)-based approaches for predicting content-optimized convex hulls across multiple codec settings. The considered methods are evaluated on our proposed large-scale dataset, which includes 300 UHD video shots encoded with software and hardware encoders using three state-of-the-art video standards, including AVC\/H.264, HEVC\/H.265, and VVC\/H.266, at various bitrate points. Our analysis provides valuable insights and establishes baseline performance for future research in this field (\n            <jats:italic toggle=\"yes\">Dataset URL<\/jats:italic>\n            :\n            <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/nasext-vaader.insa-rennes.fr\/ietr-vaader\/datasets\/br_ladder)\">https:\/\/nasext-vaader.insa-rennes.fr\/ietr-vaader\/datasets\/br_ladder<\/jats:ext-link>\n            ).\n          <\/jats:p>","DOI":"10.1145\/3723006","type":"journal-article","created":{"date-parts":[[2025,3,12]],"date-time":"2025-03-12T12:04:03Z","timestamp":1741781043000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Convex Hull Prediction Methods for Bitrate Ladder Construction: Design, Evaluation, and Comparison"],"prefix":"10.1145","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-0811-507X","authenticated-orcid":false,"given":"Ahmed","family":"Telili","sequence":"first","affiliation":[{"name":"University of Rennes, INSA Rennes, CNRS, IETR\u2013UMR 6164, Rennes, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0143-1756","authenticated-orcid":false,"given":"Wassim","family":"Hamidouche","sequence":"additional","affiliation":[{"name":"University of Rennes, INSA Rennes, CNRS, IETR\u2013UMR 6164, Rennes, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9853-1720","authenticated-orcid":false,"given":"Hadi","family":"Amirpour","sequence":"additional","affiliation":[{"name":"Christian Doppler Laboratory ATHENA, Alpen-Adria-Universit\u00e4t Klagenfurt, Klagenfurt, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6453-8588","authenticated-orcid":false,"given":"Sid Ahmed","family":"Fezza","sequence":"additional","affiliation":[{"name":"National Higher School of Telecommunications and ICT, Oran, Algeria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0031-5243","authenticated-orcid":false,"given":"Christian","family":"Timmerer","sequence":"additional","affiliation":[{"name":"Christian Doppler Laboratory ATHENA, Alpen-Adria-Universit\u00e4t, Klagenfurt, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8241-1425","authenticated-orcid":false,"given":"Luce","family":"Morin","sequence":"additional","affiliation":[{"name":"University of Rennes, INSA Rennes, CNRS, IETR\u2013UMR 6164, Rennes, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,7,18]]},"reference":[{"key":"e_1_3_1_2_2","unstructured":"FFmpeg. 2023. 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