SURVANT: An Innovative Semantics-Based Surveillance Video Archives Investigation Assistant

G. Vella; A. Dimou; D. Gutierrez-Perez; Daniele Toti; T. Nicoletti; Mattina E. La; F. Grassi; A. Ciapetti; M. McElligott; N. Shahid; P. Daras

doi:10.1007/978-3-030-68787-8_44

SURVANT: An Innovative Semantics-Based Surveillance Video Archives Investigation Assistant

G. Vella^*
, A. Dimou
, D. Gutierrez-Perez
, Daniele Toti
, T. Nicoletti
, Mattina E. La
, F. Grassi
, A. Ciapetti
, M. McElligott
, N. Shahid
, P. Daras

^*Autore corrispondente per questo lavoro

Risultato della ricerca: Contributo in libro › Contributo a conferenza

Abstract

SURVANT is an innovative video archive investigation system that aims to drastically reduce the time required to examine large amounts of video content. It can collect the videos relevant to a specific case from heterogeneous repositories in a seamless manner. SURVANT employs Deep Learning technologies to extract inter/intra-camera video analytics, including object recognition, inter/intra-camera tracking, and activity detection. The identified entities are semantically indexed enabling search and retrieval of visual characteristics. Semantic reasoning and inference mechanisms based on visual concepts and spatio-temporal metadata allows users to identify hidden correlations and discard outliers. SURVANT offers the user a unified GIS-based search interface to unearth the required information using natural language query expressions and a plethora of filtering options. An intuitive interface with a relaxed learning curve assists the user to create specific queries and receive accurate results using advanced visual analytics tools. GDPR compliant management of personal data collected from surveillance videos is integrated in the system design.

Lingua originale	Inglese
Titolo della pubblicazione ospite	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Editore	Springer Science and Business Media Deutschland GmbH
Pagine	611-626
Numero di pagine	16
Volume	12667
ISBN (stampa)	978-3-030-68786-1
DOI	https://doi.org/10.1007/978-3-030-68787-8_44
Stato di pubblicazione	Pubblicato - 2021

All Science Journal Classification (ASJC) codes

Informatica Teorica
Informatica Generale

Keywords

Complex Query Formulator
Deep Learning
Inter/intra camera analytics
Spatio-temporal semantic reasoning
Trajectory mining

Accesso al documento

10.1007/978-3-030-68787-8_44

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Vella, G., Dimou, A., Gutierrez-Perez, D., Toti, D., Nicoletti, T., La, M. E., Grassi, F., Ciapetti, A., McElligott, M., Shahid, N., & Daras, P. (2021). SURVANT: An Innovative Semantics-Based Surveillance Video Archives Investigation Assistant. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12667, pagg. 611-626). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-68787-8_44

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abstract = "SURVANT is an innovative video archive investigation system that aims to drastically reduce the time required to examine large amounts of video content. It can collect the videos relevant to a specific case from heterogeneous repositories in a seamless manner. SURVANT employs Deep Learning technologies to extract inter/intra-camera video analytics, including object recognition, inter/intra-camera tracking, and activity detection. The identified entities are semantically indexed enabling search and retrieval of visual characteristics. Semantic reasoning and inference mechanisms based on visual concepts and spatio-temporal metadata allows users to identify hidden correlations and discard outliers. SURVANT offers the user a unified GIS-based search interface to unearth the required information using natural language query expressions and a plethora of filtering options. An intuitive interface with a relaxed learning curve assists the user to create specific queries and receive accurate results using advanced visual analytics tools. GDPR compliant management of personal data collected from surveillance videos is integrated in the system design.",

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Vella, G, Dimou, A, Gutierrez-Perez, D, Toti, D, Nicoletti, T, La, ME, Grassi, F, Ciapetti, A, McElligott, M, Shahid, N & Daras, P 2021, SURVANT: An Innovative Semantics-Based Surveillance Video Archives Investigation Assistant. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 12667, Springer Science and Business Media Deutschland GmbH, pagg. 611-626. https://doi.org/10.1007/978-3-030-68787-8_44

SURVANT: An Innovative Semantics-Based Surveillance Video Archives Investigation Assistant. / Vella, G.; Dimou, A.; Gutierrez-Perez, D. et al.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 12667 Springer Science and Business Media Deutschland GmbH, 2021. pag. 611-626.

Risultato della ricerca: Contributo in libro › Contributo a conferenza

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AU - Toti, Daniele

AU - Nicoletti, T.

AU - La, Mattina E.

AU - Grassi, F.

AU - Ciapetti, A.

AU - McElligott, M.

AU - Shahid, N.

AU - Daras, P.

PY - 2021

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N2 - SURVANT is an innovative video archive investigation system that aims to drastically reduce the time required to examine large amounts of video content. It can collect the videos relevant to a specific case from heterogeneous repositories in a seamless manner. SURVANT employs Deep Learning technologies to extract inter/intra-camera video analytics, including object recognition, inter/intra-camera tracking, and activity detection. The identified entities are semantically indexed enabling search and retrieval of visual characteristics. Semantic reasoning and inference mechanisms based on visual concepts and spatio-temporal metadata allows users to identify hidden correlations and discard outliers. SURVANT offers the user a unified GIS-based search interface to unearth the required information using natural language query expressions and a plethora of filtering options. An intuitive interface with a relaxed learning curve assists the user to create specific queries and receive accurate results using advanced visual analytics tools. GDPR compliant management of personal data collected from surveillance videos is integrated in the system design.

AB - SURVANT is an innovative video archive investigation system that aims to drastically reduce the time required to examine large amounts of video content. It can collect the videos relevant to a specific case from heterogeneous repositories in a seamless manner. SURVANT employs Deep Learning technologies to extract inter/intra-camera video analytics, including object recognition, inter/intra-camera tracking, and activity detection. The identified entities are semantically indexed enabling search and retrieval of visual characteristics. Semantic reasoning and inference mechanisms based on visual concepts and spatio-temporal metadata allows users to identify hidden correlations and discard outliers. SURVANT offers the user a unified GIS-based search interface to unearth the required information using natural language query expressions and a plethora of filtering options. An intuitive interface with a relaxed learning curve assists the user to create specific queries and receive accurate results using advanced visual analytics tools. GDPR compliant management of personal data collected from surveillance videos is integrated in the system design.

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BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

PB - Springer Science and Business Media Deutschland GmbH

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Vella G, Dimou A, Gutierrez-Perez D, Toti D, Nicoletti T, La ME et al. SURVANT: An Innovative Semantics-Based Surveillance Video Archives Investigation Assistant. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 12667. Springer Science and Business Media Deutschland GmbH. 2021. pag. 611-626 doi: 10.1007/978-3-030-68787-8_44

SURVANT: An Innovative Semantics-Based Surveillance Video Archives Investigation Assistant

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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