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Amalia.js: An Open-Source Metadata Driven HTML5 Multimedia Player

Authors:

Nicolas Hervé,

Pierre Letessier,

Mathieu Derval,

Hakim NabiAuthors Info & Claims

MM '15: Proceedings of the 23rd ACM international conference on Multimedia

Pages 709 - 712

https://doi.org/10.1145/2733373.2807406

Published: 13 October 2015 Publication History

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Abstract

Amalia.js is a new extensible and versatile HTML5 multimedia player that allows you to view any type of metadata synchronized with your video or audio streams. It manages metadata that are localized both temporally and spatially. They can also be hierarchical. Several visualization plugins have already been developped, enabling amalia.js to be deployed in a huge variety of web applications. We believe it can be used in various research areas to quickly visualize analysis results and to share them with the community. Amalia.js is an open-source software under a GPL license. It is available for download at http://ina-foss.github.io/amalia.js.

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Cited By

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Carrive JBeloued AGoetschel PHeiden SLalande SLisena PMazuet FMeignier SPincemin BTroncy R(2024)Analyse transdisciplinaire d’un corpus d’actualités filméesLes nouveaux paradigmes de l'archive10.4000/books.pan.7194Online publication date: 2024
https://doi.org/10.4000/books.pan.7194
Fonteles JDavalos EAshwin TZhang YZhou MAyalon ELane ASteinberg SAnton GDanish JEnyedy NBiswas G(2024)A First Step in Using Machine Learning Methods to Enhance Interaction Analysis for Embodied Learning EnvironmentsArtificial Intelligence in Education10.1007/978-3-031-64299-9_1(3-16)Online publication date: 2-Jul-2024
https://doi.org/10.1007/978-3-031-64299-9_1
Kato JOgata MInoue TGoto MBoll SMu Lee KLuo JZhu WByun HWen Chen CLienhart RMei T(2018)Songle SyncProceedings of the 26th ACM international conference on Multimedia10.1145/3240508.3240619(1697-1705)Online publication date: 15-Oct-2018
https://dl.acm.org/doi/10.1145/3240508.3240619

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Amalia.js: An Open-Source Metadata Driven HTML5 Multimedia Player

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Information & Contributors

Information

Published In

MM '15: Proceedings of the 23rd ACM international conference on Multimedia

October 2015

1402 pages

ISBN:9781450334594

DOI:10.1145/2733373

General Chairs:
Xiaofang Zhou
The University of Queensland, Australia
,
Alan F. Smeaton
Dublin City University, Ireland
,
Qi Tian
The University of Texas at San Antonio, USA
,
Program Chairs:
Dick C.A. Bulterman
FXPAL, USA
,
Heng Tao Shen
The University of Queensland, Australia
,
Ketan Mayer-Patel
The University of North Carolina, USA
,
Shuicheng Yan
National University of Singapore, Singapore

Permission to make digital or hard copies of all or part 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 components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 October 2015

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MM '15

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SIGMM

MM '15: ACM Multimedia Conference

October 26 - 30, 2015

Brisbane, Australia

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MM '15 Paper Acceptance Rate 56 of 252 submissions, 22%;

Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

View all

Carrive JBeloued AGoetschel PHeiden SLalande SLisena PMazuet FMeignier SPincemin BTroncy R(2024)Analyse transdisciplinaire d’un corpus d’actualités filméesLes nouveaux paradigmes de l'archive10.4000/books.pan.7194Online publication date: 2024
https://doi.org/10.4000/books.pan.7194
Fonteles JDavalos EAshwin TZhang YZhou MAyalon ELane ASteinberg SAnton GDanish JEnyedy NBiswas G(2024)A First Step in Using Machine Learning Methods to Enhance Interaction Analysis for Embodied Learning EnvironmentsArtificial Intelligence in Education10.1007/978-3-031-64299-9_1(3-16)Online publication date: 2-Jul-2024
https://doi.org/10.1007/978-3-031-64299-9_1
Kato JOgata MInoue TGoto MBoll SMu Lee KLuo JZhu WByun HWen Chen CLienhart RMei T(2018)Songle SyncProceedings of the 26th ACM international conference on Multimedia10.1145/3240508.3240619(1697-1705)Online publication date: 15-Oct-2018
https://dl.acm.org/doi/10.1145/3240508.3240619
Frisson CMalacria SBailly GDutoit TKaye JDruin ALampe CMorris DHourcade J(2016)InspectorWidgetProceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems10.1145/2851581.2892388(1548-1554)Online publication date: 7-May-2016
https://dl.acm.org/doi/10.1145/2851581.2892388

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