@article{KrizekHausleitnerBoehmeetal.,
  author    = {Krizek, Gerd Christian and Hausleitner, Rene and B{\"o}hme, Laura and Olaverri-Monreal, Cristina},
  title     = {Empirical Analysis of Safe Distance Calculation by the Stereoscopic Capturing and Processing of Images Through the Tailigator System},
  series = {sensors},
  journal   = {sensors},
  abstract  = {Driver disregard for the minimum safety distance increases the probability of rear-end collisions. In order to contribute to active safety on the road, we propose in this work a low-cost Forward Collision Warning system that captures and processes images. Using cameras located in the rear section of a leading vehicle, this system serves the purpose of discouraging tailgating behavior from the vehicle driving behind. We perform in this paper the pertinent field tests to assess system performance, focusing on the calculated distance from the processing of images and the error margins in a straight line, as well as in a curve. Based on the evaluation results, the current version of the Tailigator can be used at speeds up to 50 km per hour without any restrictions. The measurements showed similar characteristics both on the straight line and in the curve. At close distances, between 3 and 5 m, the values deviated from the real value. At average distances, around 10 to 15 m, the Tailigator achieved the best results. From distances higher than 20 m, the deviations increased steadily with the distance. We contribute to the state of the art with an innovative low-cost system to identify tailgating behavior and raise awareness, which works independently of the rear vehicle's communication capabilities or equipment.},
  subject      = {tailgating},
  language  = {en}
}
@inproceedings{WoeberTibihikaOlaverriMonrealetal.,
  author    = {W{\"o}ber, Wilfried and Tibihika, Papius D and Olaverri-Monreal, Cristina and Mehnen, Lars and Sykacek, Peter and Meimberg, Harald},
  title     = {Comparison of Unsupervised Learning Methods for Natural Image Processing},
  series = {Biodiversity Information Science and Standards},
  booktitle = {Biodiversity Information Science and Standards},
  number    = {3},
  subject      = {Machine Learning},
  language  = {en}
}
@inproceedings{WoeberAburaiaOlaverriMonreal,
  author    = {W{\"o}ber, Wilfried and Aburaia, Mohamed and Olaverri-Monreal, Cristina},
  title     = {Classification of Streetsigns Using Gaussian Process Latent Variable Models},
  series = {2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE), Graz, Austria},
  booktitle = {2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE), Graz, Austria},
  subject      = {Streetsigns},
  language  = {en}
}