@incollection{BecherForestiKauletal.2009,
  author    = {Christopher Becher and G. L. Foresti and Peter Kaul and W. Koch and F. P. Lorenz and D. Lubczyk and C. Micheloni and C. Piciarelli and K. Safenreiter and C. Siering and M. Varela and S. R. Waldvogel and M. Wieneke},
  title     = {A Security Assistance System Combining Person Tracking with Chemical Attributes and Video Event Analysis},
  series = {Zacharias, terHorst et al. (Hg.): Forschungsspitzen und Spitzenforschung. Innovationen an der FH Bonn-Rhein-Sieg, Festschrift f{\"u}r Wulf Fischer},
  publisher = {Physica-Verlag},
  address   = {Heidelberg},
  isbn      = {978-3-7908-2126-0},
  doi       = {10.1007/978-3-7908-2127-7\_25},
  pages     = {277 -- 296},
  year      = {2009},
  abstract  = {Timely recognition of threats can be significantly supported by security assistance systems that work continuously in time and call the security personnel in case of anomalous events in the surveillance area. We describe the concept and the realization of an indoor security assistance system for real-time decision support. The system consists of a computer vision module and a person classification module. The computer vision module provides a video event analysis of the entrance region in front of the demonstrator. After entering the control corridor, the persons are tracked, classified, and potential threats are localized inside the demonstrator. Data for the person classification are provided by chemical sensors detecting hazardous materials. Due to their limited spatio-temporal resolution, a single chemical sensor cannot localize this material and associate it with a person. We compensate this deficiency by fusing the output of multiple, distributed chemical sensors with kinematical data from laser-range scanners. Considering both the computer vision formation and the results of the person classification affords the localization of threats and a timely reaction of the security personnel.},
  language  = {en}
}