Removing nuisance in tracklet data

Autoren Natalia Shepeleva
Thomas Hoch
Lukas Fischer
Werner Kloihofer
Bernhard A. Moser
Editoren Henri Bouma
Radhakrishna Prabhu
Robert James Stokes
Yitzhak Yitzjaky
Titel Removing nuisance in tracklet data
Buchtitel Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies II - Proc. SPIE 2018
Typ in Konferenzband
Verlag SPIE
Band 10802
ISBN 9781510621879
DOI 10.1117/12.2325636
Monat November
Jahr 2018
Seiten 08020S
SCCH ID# 18066

In this article, the problem of the lack of robustness and reliability of surveillance systems through disturbing security irrelevant events such as tree shaking, birds flying, etc. is tackled. A novel scene analysis approach based on hypergraph-based trajectories is introduced for reducing the rate of false positives. The conception of hypergraph-based trajectories relaxes the notion of point-based trajectories by allowing multiple incidences between subsequent points in time. This allows a principled approach for the extraction of robust features based on bounding boxes resulting from existing 3rd party detection methods. The experimental part is based on data collected from single-view camera systems over a two-year non-stop recording in the frame of the Austrian KIRAS project SKIN1 on protecting critical infrastructure. The results show substantial reduction of irrelevant false alarms, hence improving the overall system’s performance.