This paper presents a revised version of the VISIONE video retrieval system, which offers a wide range of search functionalities, including free text search, spatial color and object search, visual and semantic similarity search, and temporal search. The system is designed to ensure scalability using advanced indexing techniques and effectiveness using cutting-edge Artificial Intelligence technology for visual content analysis. VISIONE was the runner-up in the 2023 Video Browser Showdown competition, demonstrating its comprehensive video retrieval capabilities. In this paper, we detail the improvements made to the search and browsing interface to enhance its usability for non-expert users. A demonstration video of our system with the restyled interface, showcasing its capabilities on over 2,300 hours of diverse video content, is available online at https://youtu.be/srD3TCUkMSg.

VISIONE for newbies: an easier-to-use video retrieval system

Amato G;Bolettieri P;Carrara F;Falchi F;Gennaro C;Messina N;Vadicamo L;Vairo C
2023

Abstract

This paper presents a revised version of the VISIONE video retrieval system, which offers a wide range of search functionalities, including free text search, spatial color and object search, visual and semantic similarity search, and temporal search. The system is designed to ensure scalability using advanced indexing techniques and effectiveness using cutting-edge Artificial Intelligence technology for visual content analysis. VISIONE was the runner-up in the 2023 Video Browser Showdown competition, demonstrating its comprehensive video retrieval capabilities. In this paper, we detail the improvements made to the search and browsing interface to enhance its usability for non-expert users. A demonstration video of our system with the restyled interface, showcasing its capabilities on over 2,300 hours of diverse video content, is available online at https://youtu.be/srD3TCUkMSg.
2023
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Inglese
Chetouani A., Bailler W., Gurrin C., Benoit A.
CBMI '23: Proceedings of the 20th International Conference on Content-based Multimedia Indexing
Contributo
CBMI 2023 - 20th International Conference on Content-based Multimedia Indexing
158
162
5
9798400709128
https://doi.org/10.1145/3617233.3617261
ACM - Association for Computing Machinery
New York
STATI UNITI D'AMERICA
Sì, ma tipo non specificato
20-22/09/2023
Orleans, France
Video search
Video retrieval
User interface
Multimedia retrieval
Interactive system
Cross-modal search
Elettronico
8
restricted
Amato, G; Bolettieri, P; Carrara, F; Falchi, F; Gennaro, C; Messina, N; Vadicamo, L; Vairo, C
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
   A European Excellence Centre for Media, Society and Democracy
   AI4Media
   H2020
   951911
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/454705
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