TY - GEN
T1 - SURVANT: An Innovative Semantics-Based Surveillance Video Archives Investigation Assistant
AU - Vella, Giuseppe
AU - Dimou, Anastasios
AU - Gutierrez-Perez, David
AU - Toti, Daniele
AU - Nicoletti, Tommaso
AU - La Mattina, Ernesto
AU - Grassi, Francesco
AU - Ciapetti, Andrea
AU - Mcelligott, Michael
AU - Shahid, Nauman
AU - Daras, Petros
PY - 2021
Y1 - 2021
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.
KW - Complex Query Formulator
KW - Deep Learning
KW - Inter/intra camera analytics
KW - Spatio-temporal semantic reasoning
KW - Trajectory mining
KW - Complex Query Formulator
KW - Deep Learning
KW - Inter/intra camera analytics
KW - Spatio-temporal semantic reasoning
KW - Trajectory mining
UR - http://hdl.handle.net/10807/178515
U2 - 10.1007/978-3-030-68787-8_44
DO - 10.1007/978-3-030-68787-8_44
M3 - Conference contribution
SN - 978-3-030-68786-1
VL - 12667
T3 - LECTURE NOTES IN COMPUTER SCIENCE
SP - 611
EP - 626
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 25th International Conference on Pattern Recognition Workshops, ICPR 2020
Y2 - 10 January 2021 through 11 January 2021
ER -