Title
Complex Threat Detection: Learning vs. Rules, using a Hierarchy of Features
Author
Burghouts, G.J.
van Slingerland, P.
ten Hove, R.J.M.
den Hollander, R.J.M.
Schutte, K.
Publication year
2014
Abstract
Theft of cargo from a truck or attacks against the driver are threats hindering the day to day operations of trucking companies. In this work we consider a system, which is using surveillance cameras mounted on the truck to provide an early warning for such evolving threats. Low-level processing involves tracking people and calculating motion features. Intermediate-level processing provides kinematics and localisation, activity descriptions and threat stage estimates. At the high level, we compare threat detection performed with a statistical trained SVM based classifier against a rule based system. Results are promising, and show that the best system depends on the scenario.
Subject
Physics & Electronics ; Communication & Information
II - Intelligent Imaging ; MNS - Media & Network Services
TS - Technical Sciences
Safety and Security
Image processing
Defence, Safety and Security
Threat detection
Video surveillance
Signal processing
Motion features
Scenarios
To reference this document use:
http://resolver.tudelft.nl/uuid:8476db8c-c892-4f97-8b84-326fd348eade
TNO identifier
513583
Publisher
IEEE, Piscataway, NJ
Source
11th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2014, 26-29 Augustus 2014, Seoul, Korea, 375-380
Document type
conference paper