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VISIONE at Video Browser Showdown 2023

Contributo in Atti di convegno
Data di Pubblicazione:
2023
Abstract:
In this paper, we present the fourth release of VISIONE, a tool for fast and effective video search on a large-scale dataset. It includes several search functionalities like text search, object and color-based search, semantic and visual similarity search, and temporal search. VISIONE uses ad-hoc textual encoding for indexing and searching video content, and it exploits a full-text search engine as search backend. In this new version of the system, we introduced some changes both to the current search techniques and to the user interface.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Content-based video retrieval; Video search; Information search and retrieval; Surrogate text representation; Multi-modal retrieval
Elenco autori:
Amato, Giuseppe; Gennaro, Claudio; Bolettieri, Paolo; Falchi, Fabrizio; Vairo, CLAUDIO FRANCESCO; Vadicamo, Lucia; Carrara, Fabio; Messina, Nicola
Autori di Ateneo:
AMATO GIUSEPPE
BOLETTIERI PAOLO
CARRARA FABIO
FALCHI FABRIZIO
GENNARO CLAUDIO
VADICAMO LUCIA
VAIRO CLAUDIO FRANCESCO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/461414
Link al Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/461414/159207/prod_486130-doc_201637.pdf
Titolo del libro:
MultiMedia Modeling
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URL

https://doi.org/10.1007/978-3-031-27077-2_48
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