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MX2019005026A - Tecnicas para mejorar la calidad de datos subjetivos. - Google Patents

Tecnicas para mejorar la calidad de datos subjetivos.

Info

Publication number
MX2019005026A
MX2019005026A MX2019005026A MX2019005026A MX2019005026A MX 2019005026 A MX2019005026 A MX 2019005026A MX 2019005026 A MX2019005026 A MX 2019005026A MX 2019005026 A MX2019005026 A MX 2019005026A MX 2019005026 A MX2019005026 A MX 2019005026A
Authority
MX
Mexico
Prior art keywords
subjective
ratings
modeling machine
optimized
factors
Prior art date
Application number
MX2019005026A
Other languages
English (en)
Other versions
MX382125B (es
Inventor
Li Zhi
Original Assignee
Netflix Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Netflix Inc filed Critical Netflix Inc
Publication of MX2019005026A publication Critical patent/MX2019005026A/es
Publication of MX382125B publication Critical patent/MX382125B/es

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N17/00—Diagnosis, testing or measuring for television systems or their details
    • H04N17/004—Diagnosis, testing or measuring for television systems or their details for digital television systems
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformations in the plane of the image
    • G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
    • G06T3/4092—Image resolution transcoding, e.g. by using client-server architectures
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/98—Detection or correction of errors, e.g. by rescanning the pattern or by human intervention; Evaluation of the quality of the acquired patterns
    • G06V10/993—Evaluation of the quality of the acquired pattern
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/49—Segmenting video sequences, i.e. computational techniques such as parsing or cutting the sequence, low-level clustering or determining units such as shots or scenes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
    • H04N21/44—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
    • H04N21/44008—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs involving operations for analysing video streams, e.g. detecting features or characteristics in the video stream
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
    • H04N21/466—Learning process for intelligent management, e.g. learning user preferences for recommending movies
    • H04N21/4662—Learning process for intelligent management, e.g. learning user preferences for recommending movies characterized by learning algorithms
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/47—End-user applications
    • H04N21/475—End-user interface for inputting end-user data, e.g. personal identification number [PIN], preference data
    • H04N21/4756—End-user interface for inputting end-user data, e.g. personal identification number [PIN], preference data for rating content, e.g. scoring a recommended movie
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30168—Image quality inspection

Landscapes

  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Signal Processing (AREA)
  • Databases & Information Systems (AREA)
  • Quality & Reliability (AREA)
  • Human Computer Interaction (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Biomedical Technology (AREA)
  • General Health & Medical Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Software Systems (AREA)
  • Computational Linguistics (AREA)
  • Computing Systems (AREA)
  • Testing, Inspecting, Measuring Of Stereoscopic Televisions And Televisions (AREA)
  • Combined Controls Of Internal Combustion Engines (AREA)
  • Testing Of Engines (AREA)

Abstract

En varias modalidades, una máquina de modelado subjetivo mitiga las inexactitudes en valoraciones subjetivas de contenido. La máquina de modelado subjetivo genera un modelo que incluye las valoraciones subjetivas de contenido además de parámetros para puntuaciones subjetivas y factores subjetivos. La máquina de modelado subjetivo inicializa los parámetros y luego realiza operaciones de optimización lo que incrementa la probabilidad que las puntuaciones subjetivas optimizadas compensen los factores subjetivos optimizados. De forma ventajosa, debido a que la máquina de modelado subjetivo optimiza conjuntamente las puntuaciones subjetivas y los factores subjetivos, las puntuaciones subjetivas optimizadas proporcionan valoraciones imparciales y consistentes de contenido digital.
MX2019005026A 2016-11-03 2017-11-03 Tecnicas para mejorar la calidad de datos subjetivos. MX382125B (es)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201662417230P 2016-11-03 2016-11-03
US15/406,617 US10586110B2 (en) 2016-11-03 2017-01-13 Techniques for improving the quality of subjective data
PCT/US2017/060045 WO2018085720A1 (en) 2016-11-03 2017-11-03 Techniques for improving the quality of subjective data

Publications (2)

Publication Number Publication Date
MX2019005026A true MX2019005026A (es) 2019-11-18
MX382125B MX382125B (es) 2025-03-13

Family

ID=62021645

Family Applications (1)

Application Number Title Priority Date Filing Date
MX2019005026A MX382125B (es) 2016-11-03 2017-11-03 Tecnicas para mejorar la calidad de datos subjetivos.

Country Status (6)

Country Link
US (1) US10586110B2 (es)
EP (1) EP3535980A1 (es)
AU (2) AU2017355533B2 (es)
CA (1) CA3042247A1 (es)
MX (1) MX382125B (es)
WO (1) WO2018085720A1 (es)

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102020000327B4 (de) * 2020-01-21 2024-06-27 Rolls-Royce Solutions GmbH Verfahren zur modellbasierten Steuerung und Regelung einer Brennkraftmaschine
US12393865B2 (en) 2020-04-13 2025-08-19 Y.E. Hub Armenia LLC Method and server for training machine learning algorithm for ranking objects
US12271826B2 (en) 2020-07-20 2025-04-08 Y.E. Hub Armenia LLC Methods and systems for training a decision-tree based Machine Learning Algorithm (MLA)
US11363275B2 (en) * 2020-07-31 2022-06-14 Netflix, Inc. Techniques for increasing the accuracy of subjective quality experiments
US12536451B2 (en) 2021-06-18 2026-01-27 Y.E. Hub Armenia LLC Methods and systems for generating an uncertainty score for an output of a gradient boosted decision tree model
US12499527B2 (en) 2023-10-04 2025-12-16 Akamai Technologies, Inc. Reference-based video quality analysis-as-a-service (VQAaaS) for over-the-top (OTT) streaming

Family Cites Families (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6876381B2 (en) 2001-01-10 2005-04-05 Koninklijke Philips Electronics N.V. System and method for providing a scalable objective metric for automatic video quality evaluation employing interdependent objective metrics
US6992697B2 (en) * 2002-06-19 2006-01-31 Koninklijke Philips Electronics N.V. Method and apparatus to measure video quality on any display device with any image size starting from a know display type and size
GB0314161D0 (en) * 2003-06-18 2003-07-23 British Telecomm Edge analysis in video quality assessment
KR100731358B1 (ko) * 2005-11-09 2007-06-21 삼성전자주식회사 화질 평가 방법 및 시스템
US8631044B2 (en) * 2008-12-12 2014-01-14 The Trustees Of Columbia University In The City Of New York Machine optimization devices, methods, and systems
US8825886B2 (en) * 2010-07-28 2014-09-02 Hong Kong Applied Science and Technology Research Institute Company Limited System and method for evaluating network transport effects on delivery of media content
JP2014077664A (ja) * 2012-10-09 2014-05-01 Ricoh Co Ltd 光沢性評価方法及び光沢性評価装置
GB2529446A (en) * 2014-07-17 2016-02-24 British Academy Of Film And Television Arts The Measurement of video quality

Also Published As

Publication number Publication date
AU2017355533B2 (en) 2021-05-06
US20180121730A1 (en) 2018-05-03
CA3042247A1 (en) 2018-05-11
AU2017355533A1 (en) 2019-05-23
AU2017355533A9 (en) 2019-06-13
WO2018085720A1 (en) 2018-05-11
AU2021212054A1 (en) 2021-08-26
MX382125B (es) 2025-03-13
EP3535980A1 (en) 2019-09-11
US10586110B2 (en) 2020-03-10

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