Document - VISIONE at Video Browser Showdown 2021

2021

Conference article Open Access

VISIONE at Video Browser Showdown 2021

Amato G., Bolettieri P., Falchi F., Gennaro C., Messina N., Vadicamo L., Vairo C.

Deep learning Content based image retrieval Video retrieval Content-Based Video Retrieval Surrogate Text Representation VBS challenge CBIR Video Search Information Search and Retrieval Large scale information retrieval

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.

Source: MMM 2021 - 27th International Conference on Multimedia Modeling, pp. 473–478, Prague, Czech Republic, 22-24/06/2021

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@inproceedings{oai:it.cnr:prodotti:454281,
	title = {VISIONE at Video Browser Showdown 2021},
	author = {Amato G. and Bolettieri P. and Falchi F. and Gennaro C. and Messina N. and Vadicamo L. and Vairo C.},
	doi = {10.1007/978-3-030-67835-7_47},
	booktitle = {MMM 2021 - 27th International Conference on Multimedia Modeling, pp. 473–478, Prague, Czech Republic, 22-24/06/2021},
	year = {2021}
}