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Article

VISIONE at Video Browser Showdown 2021

Authors:

Giuseppe Amato,

Paolo Bolettieri,

Fabrizio Falchi,

Claudio Gennaro,

Nicola Messina,

Lucia Vadicamo,

Claudio VairoAuthors Info & Claims

MultiMedia Modeling: 27th International Conference, MMM 2021, Prague, Czech Republic, June 22–24, 2021, Proceedings, Part II

Pages 473 - 478

https://doi.org/10.1007/978-3-030-67835-7_47

Published: 22 June 2021 Publication History

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.

References

[1]

Amato G et al. Kompatsiaris I, Huet B, Mezaris V, Gurrin C, Cheng W-H, Vrochidis S, et al. VISIONE at VBS2019 MultiMedia Modeling 2019 Cham Springer 591-596

[2]

Amato, G., et al.: The visione video search system: exploiting off-the-shelf text search engines for large-scale video retrieval. arXiv preprint arXiv:2008.02749 (2020)

[3]

Amato G, Carrara F, Falchi F, Gennaro C, and Vadicamo L Large-scale instance-level image retrieval Inf. Process. Manage. 2019 57 102100

[4]

Amato, G., Falchi, F., Gennaro, C., Rabitti, F.: Searching and annotating 100M images with YFCC100M-HNfc6 and MI-file. In: Proceedings of the 15th International Workshop on Content-Based Multimedia Indexing, CBMI 2017, pp. 26:1–26:4. ACM (2017)

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Berns, F., Rossetto, L., Schoeffmann, K., Beecks, C., Awad, G.: V3C1 dataset: an evaluation of content characteristics. In: Proceedings of the 2019 on International Conference on Multimedia Retrieval, ICMR 2019, pp. 334–338. Association for Computing Machinery (2019)

[6]

Bolettieri P et al. Amato G, Gennaro C, Oria V, Radovanović M, et al. An image retrieval system for video Similarity Search and Applications 2019 Cham Springer 332-339

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Kuhn HW The hungarian method for the assignment problem Naval Res. Logist. Q. 1955 2 1–2 83-97

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Lokoč J, Kovalčík G, Souček T, et al. Ro YM et al. VIRET at video browser showdown 2020 MultiMedia Modeling 2020 Cham Springer 784-789

[9]

Messina, N., Falchi, F., Esuli, A., Amato, G.: Transformer reasoning network for image-text matching and retrieval. In: International Conference on Pattern Recognition (ICPR) 2020 (2020, accepted)

[10]

Nguyen PA, Wu J, Ngo C-W, Francis D, Huet B, et al. Ro YM et al. VIREO @ video browser showdown 2020 MultiMedia Modeling 2020 Cham Springer 772-777

[11]

Rossetto L et al. Interactive video retrieval in the age of deep learning - detailed evaluation of VBS 2019 IEEE Trans. Multimed. 2021 23 243-256

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Sauter L, Amiri Parian M, Gasser R, Heller S, Rossetto L, Schuldt H, et al. Ro YM et al. Combining boolean and multimedia retrieval in vitrivr for large-scale video search MultiMedia Modeling 2020 Cham Springer 760-765

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Schoeffmann, K.: Video browser showdown 2012–2019: a review. In: 2019 International Conference on Content-Based Multimedia Indexing (CBMI), pp. 1–4 (2019)

[14]

Tolias, G., Sicre, R., Jégou, H.: Particular object retrieval with integral max-pooling of CNN activations. arXiv preprint arXiv:1511.05879 (2015)

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Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, pp. 5998–6008 (2017)

Cited By

Amato GBolettieri PCarrara FFalchi FGennaro CMessina NVadicamo LVairo C(2023)VISIONE for newbies: an easier-to-use video retrieval systemProceedings of the 20th International Conference on Content-based Multimedia Indexing10.1145/3617233.3617261(158-162)Online publication date: 20-Sep-2023
https://dl.acm.org/doi/10.1145/3617233.3617261
Amato GBolettieri PCarrara FFalchi FGennaro CMessina NVadicamo LVairo C(2023)VISIONE: A Large-Scale Video Retrieval System with Advanced Search FunctionalitiesProceedings of the 2023 ACM International Conference on Multimedia Retrieval10.1145/3591106.3592226(649-653)Online publication date: 12-Jun-2023
https://dl.acm.org/doi/10.1145/3591106.3592226
Lokoč JAndreadis SBailer WDuane AGurrin CMa ZMessina NNguyen TPeška LRossetto LSauter LSchall KSchoeffmann KKhan OSpiess FVadicamo LVrochidis S(2023)Interactive video retrieval in the age of effective joint embedding deep models: lessons from the 11th VBSMultimedia Systems10.1007/s00530-023-01143-529:6(3481-3504)Online publication date: 1-Dec-2023
https://dl.acm.org/doi/10.1007/s00530-023-01143-5
Show More Cited By

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Information & Contributors

Information

Published In

cover image Guide Proceedings

MultiMedia Modeling: 27th International Conference, MMM 2021, Prague, Czech Republic, June 22–24, 2021, Proceedings, Part II

Jun 2021

524 pages

ISBN:978-3-030-67834-0

DOI:10.1007/978-3-030-67835-7

Editors:
Jakub Lokoč
Charles University, Prague, Czech Republic
,
Tomáš Skopal
Charles University, Prague, Czech Republic
,
Klaus Schoeffmann
Klagenfurt University, Klagenfurt, Austria
,
Vasileios Mezaris
CERTH-ITI, Thessaloniki, Greece
,
Xirong Li
Renmin University of China, Beijing, China
,
Stefanos Vrochidis
CERTH-ITI, Thessaloniki, Greece
,
Ioannis Patras
Queen Mary University of London, London, UK

© Springer Nature Switzerland AG 2021.

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 22 June 2021

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Cited By

Amato GBolettieri PCarrara FFalchi FGennaro CMessina NVadicamo LVairo C(2023)VISIONE for newbies: an easier-to-use video retrieval systemProceedings of the 20th International Conference on Content-based Multimedia Indexing10.1145/3617233.3617261(158-162)Online publication date: 20-Sep-2023
https://dl.acm.org/doi/10.1145/3617233.3617261
Amato GBolettieri PCarrara FFalchi FGennaro CMessina NVadicamo LVairo C(2023)VISIONE: A Large-Scale Video Retrieval System with Advanced Search FunctionalitiesProceedings of the 2023 ACM International Conference on Multimedia Retrieval10.1145/3591106.3592226(649-653)Online publication date: 12-Jun-2023
https://dl.acm.org/doi/10.1145/3591106.3592226
Lokoč JAndreadis SBailer WDuane AGurrin CMa ZMessina NNguyen TPeška LRossetto LSauter LSchall KSchoeffmann KKhan OSpiess FVadicamo LVrochidis S(2023)Interactive video retrieval in the age of effective joint embedding deep models: lessons from the 11th VBSMultimedia Systems10.1007/s00530-023-01143-529:6(3481-3504)Online publication date: 1-Dec-2023
https://dl.acm.org/doi/10.1007/s00530-023-01143-5
Amato GBolettieri PCarrara FFalchi FGennaro CMessina NVadicamo LVairo C(2023)VISIONE at Video Browser Showdown 2023MultiMedia Modeling10.1007/978-3-031-27077-2_48(615-621)Online publication date: 9-Jan-2023
https://dl.acm.org/doi/10.1007/978-3-031-27077-2_48
Lokoč JPeška L(2023)A Study of a Cross-modal Interactive Search Tool Using CLIP and Temporal FusionMultiMedia Modeling10.1007/978-3-031-27077-2_31(397-408)Online publication date: 9-Jan-2023
https://dl.acm.org/doi/10.1007/978-3-031-27077-2_31
Ma ZNgo CMagalhães Jdel Bimbo ASatoh SSebe NAlameda-Pineda XJin QOria VToni L(2022)Interactive Video Corpus Moment Retrieval using Reinforcement LearningProceedings of the 30th ACM International Conference on Multimedia10.1145/3503161.3548277(296-306)Online publication date: 10-Oct-2022
https://dl.acm.org/doi/10.1145/3503161.3548277
Tran MHoang-Xuan NTrang-Trung HLe TTran MLe MLe TNinh VGurrin C(2022)V-FIRST: A Flexible Interactive Retrieval System for Video at VBS 2022MultiMedia Modeling10.1007/978-3-030-98355-0_55(562-568)Online publication date: 6-Jun-2022
https://dl.acm.org/doi/10.1007/978-3-030-98355-0_55
Amato GBolettieri PCarrara FFalchi FGennaro CMessina NVadicamo LVairo C(2022)VISIONE at Video Browser Showdown 2022MultiMedia Modeling10.1007/978-3-030-98355-0_52(543-548)Online publication date: 6-Jun-2022
https://dl.acm.org/doi/10.1007/978-3-030-98355-0_52
Nguyen TPuangthamawathanakun BHealy GNguyen BGurrin CCaputo A(2022)Videofall - A Hierarchical Search Engine for VBS2022MultiMedia Modeling10.1007/978-3-030-98355-0_48(518-523)Online publication date: 6-Jun-2022
https://dl.acm.org/doi/10.1007/978-3-030-98355-0_48
Lokoč JMejzlík FSouček TDokoupil PPeška L(2022)Video Search with Context-Aware Ranker and Relevance FeedbackMultiMedia Modeling10.1007/978-3-030-98355-0_46(505-510)Online publication date: 6-Jun-2022
https://dl.acm.org/doi/10.1007/978-3-030-98355-0_46
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