Complex Threat Detection: Learning vs. Rules, using a Hierarchy of Features
conference paper
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.
TNO Identifier
513583
Publisher
IEEE
Source title
11th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2014, 26-29 Augustus 2014, Seoul, Korea
Place of publication
Piscataway, NJ
Pages
375-380
Files
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