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.
Vella, G., Dimou, A., Gutierrez-Perez, D., Toti, D., Nicoletti, T., La Mattina, E., Grassi, F., Ciapetti, A., Mcelligott, M., Shahid, N., Daras, P., 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), (Virtuale, 10-11 January 2021), Springer Science and Business Media Deutschland GmbH, Berlin 2021:<<LECTURE NOTES IN COMPUTER SCIENCE>>,12667 611-626. [10.1007/978-3-030-68787-8_44] [http://hdl.handle.net/10807/178515]
SURVANT: An Innovative Semantics-Based Surveillance Video Archives Investigation Assistant
Toti, Daniele;
2021
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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