VideoGraph – Towards Using Knowledge Graphs for Interactive Video Retrieval

Rossetto, Luca; Baumgartner, Matthias; Ashena, Narges; Ruosch, Florian; Pernisch, Romana; Heitz, Lucien; Bernstein, Abraham

doi:10.1007/978-3-030-67835-7_38

Cited by 8 publications

(3 citation statements)

References 10 publications

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“…Based on existing works [12,26,34], a mapping of the complexity of AV archive metadata in various dimensions is made and summarised in Figure 1.…”

Section: Methods and Experiments 31 A Model For Dataficationmentioning

confidence: 99%

Encoding and Decoding Narratives: Datafication and Alternative Access Models for Audiovisual Archives

Yang

2023

Proceedings of the 31st ACM International Conference on Multimedia

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Situated in the intersection of audiovisual archives, computational methods, and immersive interactions, this work probes the increasingly important accessibility issues from a two-fold approach. Firstly, the work proposes an ontological data model to handle complex descriptors (metadata, feature vectors, etc.) with regard to user interactions. Secondly, this work examines text-to-video retrieval from an implementation perspective by proposing a classifier-enhanced workflow to deal with complex and hybrid queries and a training data augmentation workflow to improve performance. This work serves as the foundation for experimenting with novel public-facing access models to large audiovisual archives. CCS CONCEPTS• Applied computing → Arts and humanities; • Information systems → Multimedia information systems; Information retrieval; • Human-centered computing → Human computer interaction (HCI).

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“…Based on existing works [12,26,34], a mapping of the complexity of AV archive metadata in various dimensions is made and summarised in Figure 1.…”

Section: Methods and Experiments 31 A Model For Dataficationmentioning

confidence: 99%

Encoding and Decoding Narratives: Datafication and Alternative Access Models for Audiovisual Archives

Yang

2023

Proceedings of the 31st ACM International Conference on Multimedia

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“…From the classic ones like production time to the more recent ones like 3D reconstruction of a specific scene [15], the increasing volume and complexity of data in AV archives make managing such assets a rough task. Based on existing works [16,17,18], a mapping of the complexity of AV archive metadata in various dimensions is made and summarised in Fig. 1.…”

Section: An Ontological Model For Av Archive Dataficationmentioning

confidence: 99%

Toward an Ontological Model for Audiovisual Archive Datafication

Yang

2023

archiving

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With the initiatives like Collections as Data and Computational Archival Science, archives are no longer seen as a static documentation of objects, but evolving sources of cultural and historical data. This work emphasizes the potential updates in preserving and documenting digital audiovisual (AV) content from a data perspective, considering the recent developments in natural language processing and computer vision tasks, as well as the emergence of interactive and embodied experiences and interfaces for innovatively accessing archival content. As part of Swiss national scientific fund Sinergia project, this work was able to work end-to-end with real-world AV archives like Télévision Suisse Romande (RTS). Resorting to an updated narrative model for mapping data that can be obtained from the content as well as the consumer, this work proposed an experimental attempt to build an ontology to formally sum up the potential new paradigm for preservation and accessibility from a data perspective for modern archives, in the hope for nurturing a digital and data driven mind-set for archive practices.

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“…The following provides an overview of the improvements made to the LifeGraph system, based on insights gained from both the previous Lifelog Search Challenge as well as related activities in the context of the Video Browser Showdown [16,19], for which we investigated the use of Knowledge Graph structures for video retrieval [15]. 1 https://blazegraph.com/ 2 https://nginx.org/ 3 https://www.w3.org/TR/sparql11-query/#propertypaths…”

Section: Improvementsmentioning

confidence: 99%

Exploring Graph-querying approaches in LifeGraph

Rossetto

Baumgartner

Gasser

et al. 2021

Proceedings of the 4th Annual on Lifelog Search Challenge

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The multi-modal and interrelated nature of lifelog data makes it well suited for graph-based representations. In this paper, we present the second iteration of LifeGraph, a Knowledge Graph for Lifelog Data, initially introduced during the 3 rd Lifelog Search Challenge in 2020. This second iteration incorporates several lessons learned from the previous version. While the actual graph has undergone only small changes, the mechanisms by which it is traversed during querying as well as the underlying storage system which performs the traversal have been changed. The means for query formulation have also been slightly extended in capability and made more efficient and intuitive. All these changes have the aim of improving result quality and reducing query time. CCS CONCEPTS• Information systems → Ontologies; Users and interactive retrieval; Specialized information retrieval; Content analysis and feature selection.

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VideoGraph – Towards Using Knowledge Graphs for Interactive Video Retrieval

Cited by 8 publications

References 10 publications

Encoding and Decoding Narratives: Datafication and Alternative Access Models for Audiovisual Archives

Encoding and Decoding Narratives: Datafication and Alternative Access Models for Audiovisual Archives

Toward an Ontological Model for Audiovisual Archive Datafication

Exploring Graph-querying approaches in LifeGraph

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