Providing video annotations in multimedia containers for visualization and research
Autor(en): | Schoning, J. Faion, P. Heidemann, G. Krumnack, U. |
Stichwörter: | Computer vision; Containers; Electronic document exchange; Learning systems; Metadata; Motion Picture Experts Group standards; Visualization, Eye-tracking; Media players; Multimedia player; Prototype implementations; Standardized methods; Video annotations; Video data, Data visualization | Erscheinungsdatum: | 2017 | Herausgeber: | Institute of Electrical and Electronics Engineers Inc. | Journal: | Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017 | Startseite: | 650 | Seitenende: | 659 | Zusammenfassung: | There is an ever increasing amount of video data sets which comprise additional metadata, such as object labels, tagged events, or gaze data. Unfortunately, metadata are usually stored in separate files in custom-made data formats, which reduces accessibility even for experts and makes the data inaccessible for non-experts. Consequently, we still lack interfaces for many common use cases, such as visualization, streaming, data analysis, machine learning, high-level understanding and semantic web integration. To bridge this gap, we want to promote the use of existing multimedia container formats to establish a standardized method of incorporating content and metadata. This will facilitate visualization in standard multimedia players, streaming via the Internet, and easy use without conversion, as shown in the attached demonstration video and files. In two prototype implementations, we embed object labels, gaze data from eye-Tracking and the corresponding video into a single multimedia container and visualize this data using a media player. Based on this prototype, we discuss the benefit of our approach as a possible standard. Finally, we argue for the inclusion of MPEG-7 in multimedia containers as a further improvement. © 2017 IEEE. |
Beschreibung: | Conference of 17th IEEE Winter Conference on Applications of Computer Vision, WACV 2017 ; Conference Date: 24 March 2017 Through 31 March 2017; Conference Code:127784 |
ISBN: | 9781509048229 | DOI: | 10.1109/WACV.2017.78 | Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016134466&doi=10.1109%2fWACV.2017.78&partnerID=40&md5=13c7a1070a1088dfac3d2b3cb2f0af52 |
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geprüft am 01.06.2024