TY - GEN
T1 - VideoGraph – Towards Using Knowledge Graphs for Interactive Video Retrieval
AU - Rossetto, L.
AU - Baumgartner, M.
AU - Ashena, N.
AU - Ruosch, F.
AU - Pernisch, R.
AU - Heitz, L.
AU - Bernstein, A.
PY - 2021
Y1 - 2021
N2 - © 2021, Springer Nature Switzerland AG.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.
AB - © 2021, Springer Nature Switzerland AG.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.
U2 - 10.1007/978-3-030-67835-7_38
DO - 10.1007/978-3-030-67835-7_38
M3 - Conference contribution
SN - 9783030678340
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 417
EP - 422
BT - MultiMedia Modeling - 27th International Conference, MMM 2021, Proceedings
A2 - Lokoc, J.
A2 - Skopal, T.
A2 - Schoeffmann, K.
A2 - Mezaris, V.
A2 - Li, X.
A2 - Vrochidis, S.
A2 - Patras, I.
PB - Springer Science and Business Media Deutschland GmbH
T2 - 27th International Conference on MultiMedia Modeling, MMM 2021
Y2 - 22 June 2021 through 24 June 2021
ER -