Articolo in rivista, 2021, ENG, 10.3390/jimaging7050076

The VISIONE video search system: exploiting off-the-shelf text search engines for large-scale video retrieval

Amato G.; Bolettieri P.; Carrara F.; Debole F.; Falchi F.; Gennaro C.; Vadicamo L.; Vairo C.

CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy

This paper describes in detail VISIONE, a video search system that allows users to search for videos using textual keywords, the occurrence of objects and their spatial relationships, the occurrence of colors and their spatial relationships, and image similarity. These modalities can be combined together to express complex queries and meet users' needs. The peculiarity of our approach is that we encode all information extracted from the keyframes, such as visual deep features, tags, color and object locations, using a convenient textual encoding that is indexed in a single text retrieval engine. This offers great flexibility when results corresponding to various parts of the query (visual, text and locations) need to be merged. In addition, we report an extensive analysis of the retrieval performance of the system, using the query logs generated during the Video Browser Showdown (VBS) 2019 competition. This allowed us to fine-tune the system by choosing the optimal parameters and strategies from those we tested.

JOURNAL OF IMAGING 7 (5)

Keywords

Content-based video retrieval, Surrogate text representation, Known item search, Ad-hoc video search, Multimedia and multimodal retrieval, Multimedia information systems, Information systems applications, Video search, Image search, Users and interactive retrieval, Retrieval models and ranking, Users and interactive retrieval

CNR authors

Carrara Fabio, Amato Giuseppe, Gennaro Claudio, Debole Franca, Bolettieri Paolo, Falchi Fabrizio, Vairo Claudio Francesco, Vadicamo Lucia

CNR institutes

ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"

ID: 456298

Year: 2021

Type: Articolo in rivista

Creation: 2021-09-02 12:05:34.000

Last update: 2023-04-20 20:39:31.000

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:456298

DOI: 10.3390/jimaging7050076

Scopus: 2-s2.0-85107488810

ISI Web of Science (WOS): 000654268900001