@article{RisseKruegelBackhaus2022,
  author    = {Risse, Sarah and Kr{\"u}gel, Andre and Backhaus, Daniel},
  title     = {Open Education in Methods Training},
  series = {Psychologische Rundschau : offizielles Organ der Deutschen Gesellschaft f{\"u}r Psychologie},
  volume    = {73},
  journal   = {Psychologische Rundschau : offizielles Organ der Deutschen Gesellschaft f{\"u}r Psychologie},
  number    = {3},
  publisher = {HOGREFE VERLAG},
  address   = {G{\"o}ttingen},
  issn      = {0033-3042},
  doi       = {10.1026/0033-3042/a000602},
  pages     = {206 -- 208},
  year      = {2022},
  language  = {en}
}
@misc{BackhausEngbertRothkegeletal.2020,
  author    = {Backhaus, Daniel and Engbert, Ralf and Rothkegel, Lars Oliver Martin and Trukenbrod, Hans Arne},
  title     = {Task-dependence in scene perception: Head unrestrained viewing using mobile eye-tracking},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe},
  number    = {5},
  issn      = {1866-8364},
  doi       = {10.25932/publishup-51912},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-519124},
  pages     = {23},
  year      = {2020},
  abstract  = {Real-world scene perception is typically studied in the laboratory using static picture viewing with restrained head position. Consequently, the transfer of results obtained in this paradigm to real-word scenarios has been questioned. The advancement of mobile eye-trackers and the progress in image processing, however, permit a more natural experimental setup that, at the same time, maintains the high experimental control from the standard laboratory setting. We investigated eye movements while participants were standing in front of a projector screen and explored images under four specific task instructions. Eye movements were recorded with a mobile eye-tracking device and raw gaze data were transformed from head-centered into image-centered coordinates. We observed differences between tasks in temporal and spatial eye-movement parameters and found that the bias to fixate images near the center differed between tasks. Our results demonstrate that current mobile eye-tracking technology and a highly controlled design support the study of fine-scaled task dependencies in an experimental setting that permits more natural viewing behavior than the static picture viewing paradigm.},
  language  = {en}
}
@article{BackhausEngbertRothkegeletal.2020,
  author    = {Backhaus, Daniel and Engbert, Ralf and Rothkegel, Lars Oliver Martin and Trukenbrod, Hans Arne},
  title     = {Task-dependence in scene perception: Head unrestrained viewing using mobile eye-tracking},
  series = {Journal of vision},
  volume    = {20},
  journal   = {Journal of vision},
  number    = {5},
  publisher = {Association for Research in Vision and Opthalmology},
  address   = {Rockville},
  issn      = {1534-7362},
  doi       = {10.1167/jov.20.5.3},
  pages     = {1 -- 21},
  year      = {2020},
  abstract  = {Real-world scene perception is typically studied in the laboratory using static picture viewing with restrained head position. Consequently, the transfer of results obtained in this paradigm to real-word scenarios has been questioned. The advancement of mobile eye-trackers and the progress in image processing, however, permit a more natural experimental setup that, at the same time, maintains the high experimental control from the standard laboratory setting. We investigated eye movements while participants were standing in front of a projector screen and explored images under four specific task instructions. Eye movements were recorded with a mobile eye-tracking device and raw gaze data were transformed from head-centered into image-centered coordinates. We observed differences between tasks in temporal and spatial eye-movement parameters and found that the bias to fixate images near the center differed between tasks. Our results demonstrate that current mobile eye-tracking technology and a highly controlled design support the study of fine-scaled task dependencies in an experimental setting that permits more natural viewing behavior than the static picture viewing paradigm.},
  language  = {en}
}
@article{SchwetlickBackhausEngbert2023,
  author    = {Schwetlick, Lisa and Backhaus, Daniel and Engbert, Ralf},
  title     = {A dynamical scan-path model for task-dependence during scene viewing},
  series = {Psychological review},
  volume    = {130},
  journal   = {Psychological review},
  number    = {3},
  publisher = {American Psychological Association},
  address   = {Washington},
  issn      = {0033-295X},
  doi       = {10.1037/rev0000379},
  pages     = {807 -- 840},
  year      = {2023},
  abstract  = {In real-world scene perception, human observers generate sequences of fixations to move image patches into the high-acuity center of the visual field. Models of visual attention developed over the last 25 years aim to predict two-dimensional probabilities of gaze positions for a given image via saliency maps. Recently, progress has been made on models for the generation of scan paths under the constraints of saliency as well as attentional and oculomotor restrictions. Experimental research demonstrated that task constraints can have a strong impact on viewing behavior. Here, we propose a scan-path model for both fixation positions and fixation durations, which include influences of task instructions and interindividual differences. Based on an eye-movement experiment with four different task conditions, we estimated model parameters for each individual observer and task condition using a fully Bayesian dynamical modeling framework using a joint spatial-temporal likelihood approach with sequential estimation. Resulting parameter values demonstrate that model properties such as the attentional span are adjusted to task requirements. Posterior predictive checks indicate that our dynamical model can reproduce task differences in scan-path statistics across individual observers.},
  language  = {en}
}