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

Autor: Tommaso Nicoletti, Daniele Toti, Ernesto La Mattina, Nauman Shahid, Anastasios Dimou, Petros Daras, Andrea Ciapetti, Michael McElligott, Francesco Grassi, David Gutierrez-Perez, Giuseppe Vella
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Pattern Recognition. ICPR International Workshops and Challenges ISBN: 9783030687861
ICPR Workshops (7)
Popis: 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.
Databáze: OpenAIRE