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Subtitle positioning for e-learning videos based on rough gaze estimation and saliency detection

Authors:

Yunfei ShenAuthors Info & Claims

SA '17: SIGGRAPH Asia 2017 Posters

Article No.: 15, Pages 1 - 2

https://doi.org/10.1145/3145690.3145735

Published: 27 November 2017 Publication History

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Abstract

Subtitle is very common shown in a variety categories of videos, especially useful as translated subtitles for native speakers. Traditional subtitle is placed at the bottom of videos in order to prevent from occluding essential video contents. However, traversing between important video contents and subtitle frequently will have a negative impact on focusing watching video itself. Recently, some research work try more flexible subtitle positioning strategy. However, these methods are effective with restrictions on the video content and devices adopted. In this work, we propose a novel subtitle content organization and placement framework based on rough gaze estimation and saliency detection.

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Cited By

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May LOhshiro KDang KSridhar SPai JFuentes MLee SCartwright M(2024)Unspoken Sound: Identifying Trends in Non-Speech Audio Captioning on YouTubeProceedings of the CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642162(1-19)Online publication date: 11-May-2024
https://doi.org/10.1145/3613904.3642162
Amin AHassan SLee SHuenerfauth M(2022)Watch It, Don’t Imagine It: Creating a Better Caption-Occlusion Metric by Collecting More Ecologically Valid Judgments from DHH ViewersProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3517681(1-14)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3517681
Amin AHassan SHuenerfauth MVazquez SDrake TAhmetovic DYaneva V(2021)Caption-occlusion severity judgments across live-television genres from deaf and hard-of-hearing viewersProceedings of the 18th International Web for All Conference10.1145/3430263.3452429(1-12)Online publication date: 19-Apr-2021
https://dl.acm.org/doi/10.1145/3430263.3452429
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Index Terms

Subtitle positioning for e-learning videos based on rough gaze estimation and saliency detection
1. Applied computing
  1. Education
    1. E-learning
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods
      1. User studies
    2. Interaction devices
      1. Displays and imagers

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Published In

SA '17: SIGGRAPH Asia 2017 Posters

November 2017

114 pages

ISBN:9781450354059

DOI:10.1145/3145690

Conference Chairs:
Diego Gutierrez
University of Zaragoza, Spain
,
Hui Huang
Shenzhen University, China

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

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Published: 27 November 2017

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the Open Project Program of the State Key Lab of CAD&CG, Zhejiang University
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SIGGRAPH

SA '17: SIGGRAPH Asia 2017

November 27 - 30, 2017

Bangkok, Thailand

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Overall Acceptance Rate 178 of 869 submissions, 20%

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May LOhshiro KDang KSridhar SPai JFuentes MLee SCartwright M(2024)Unspoken Sound: Identifying Trends in Non-Speech Audio Captioning on YouTubeProceedings of the CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642162(1-19)Online publication date: 11-May-2024
https://doi.org/10.1145/3613904.3642162
Amin AHassan SLee SHuenerfauth M(2022)Watch It, Don’t Imagine It: Creating a Better Caption-Occlusion Metric by Collecting More Ecologically Valid Judgments from DHH ViewersProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3517681(1-14)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3517681
Amin AHassan SHuenerfauth MVazquez SDrake TAhmetovic DYaneva V(2021)Caption-occlusion severity judgments across live-television genres from deaf and hard-of-hearing viewersProceedings of the 18th International Web for All Conference10.1145/3430263.3452429(1-12)Online publication date: 19-Apr-2021
https://dl.acm.org/doi/10.1145/3430263.3452429
Amin AGlasser AKushalnagar RVogler CHuenerfauth M(2021)Preferences of Deaf or Hard of Hearing Users for Live-TV Caption AppearanceUniversal Access in Human-Computer Interaction. Access to Media, Learning and Assistive Environments10.1007/978-3-030-78095-1_15(189-201)Online publication date: 24-Jul-2021
https://dl.acm.org/doi/10.1007/978-3-030-78095-1_15

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Appearance-Based Gaze Estimation Using Visual Saliency

Eye-Model-Based Gaze Estimation by RGB-D Camera

Visual Gaze Estimation by Joint Head and Eye Information

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