Not logged in.

Contribution Details

Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings Yes
Title VideoGraph – Towards Using Knowledge Graphs for Interactive Video Retrieval
Organization Unit
  • Luca Rossetto
  • Matthias Baumgartner
  • Narges Ashena
  • Florian Ruosch
  • Romana Pernisch
  • Lucien Heitz
  • Abraham Bernstein
Presentation Type paper
Item Subtype Original Work
Refereed Yes
Status Published in final form
  • English
Page Range 417 - 422
Event Title International Conference on Multimedia Modeling
Event Type conference
Event Location Prague
Event Start Date July 22 - 2021
Event End Date July 24 - 2021
Publisher Springer
Abstract Text Video is a very expressive medium, able to capture a wide variety of information in different ways. While there have been many advances in the recent past, which enable the annotation of semantic concepts as well as individual objects within video, their larger context has so far not extensively been used for the purpose of retrieval. In this paper, we introduce the first iteration of VideoGraph, a knowledge graph-based video retrieval system. VideoGraph combines information extracted from multiple video modalities with external knowledge bases to produce a semantically enriched representation of the content in a video collection, which can then be retrieved using graph traversal. For the 2021 Video Browser Showdown, we show the first proof-of-concept of such a graph-based video retrieval approach. Keywords Interactive video retrieval Knowledge-graphs Multi-modal graphs
Related URLs
Digital Object Identifier 10.1007/978-3-030-67835-7_38
Other Identification Number merlin-id:20802
PDF File Download from ZORA
Export BibTeX