Data di Pubblicazione:
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.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Video retrieval; CBIR; Deep learning; Large scale information retrieval; VBS challenge; Content based image retrieval
Elenco autori:
Messina, Nicola; Amato, Giuseppe; Gennaro, Claudio; Bolettieri, Paolo; Falchi, Fabrizio; Vairo, CLAUDIO FRANCESCO; Vadicamo, Lucia
Link alla scheda completa:
Link al Full Text:
Titolo del libro:
MultiMedia Modeling