Research Project
SURVANT - Assisting investigators to search efficiently heterogeneous video archives
A surveillance system supporting investigators to detect criminal activities by using advanced video analysis techniques.
Where: international
Where: international
Challenge
Current procedures for investigating video archives are time-consuming. Existing systems are limited to the use of single platforms and do not allow the use of heterogeneous/distributed archives. Most of them do not offer the flexibility to search for and retrieve specific incidents, security events, and dangerous behaviors, allowing the extraction of only a small list of objects.
Approach
SURVANT research project responds to the need for novel tools able to exploit spatio-temporal relationships and connections among video footages coming from the analysis of multi-camera video of several video archives to automatically support law enforcement authorities in their fight against crime and terrorism enabling the custody of the chain of evidence for the court.
Digital Ecosystem
Solution
Digital Ecosystem
SURVANT offers an innovative surveillance system with a unified interface that enables evidence extraction from heterogeneous video archives and assists the user in creating advanced search queries that can combine time, location, objects, and actions using semantic reasoning techniques. Intelligent investigation assistance features dramatically improve investigator efficiency while treating personal data ethically. Engineering coordinated the design and definition of the system architecture. It was responsible for the anonymization, privacy and data protection processes and for demonstrating the prototype in an operational environment.
The project has received co-funding from the European Union's Horizon 2020 programme FTIPilot-2015-1 - Contract N. 720417.
Results
Semantic reasoning on events extracted from footage
Trajectory Mining
Privacy by design approach
Novel GUI for an optimized user experience.
Technologies
AI & Data
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