This paper presents the second release of VISIONE, a tool for effective video search on large-scale collections. It allows users to search for videos using textual descriptions, keywords, occurrence of objects and their spatial relationships, occurrence of colors and their spatial relationships, and image similarity. One of the main features of our system is that it employs specially designed textual encodings for indexing and searching video content using the mature and scalable Apache Lucene full-text search engine.

VISIONE at Video Browser Showdown 2021

Amato G;Bolettieri P;Falchi F;Gennaro C;Messina N;Vadicamo L;Vairo C
2021

Abstract

This paper presents the second release of VISIONE, a tool for effective video search on large-scale collections. It allows users to search for videos using textual descriptions, keywords, occurrence of objects and their spatial relationships, occurrence of colors and their spatial relationships, and image similarity. One of the main features of our system is that it employs specially designed textual encodings for indexing and searching video content using the mature and scalable Apache Lucene full-text search engine.
2021
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
978-3-030-67835-7
Video retrieval
CBIR
Deep learning
Large scale information retrieval
VBS challenge
Content based image retrieval
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Descrizione: VISIONE at Video Browser Showdown 2021
Tipologia: Versione Editoriale (PDF)
Dimensione 1.23 MB
Formato Adobe PDF
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/398250
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