Least-Squares Fitting of Two 3-D Point Sets
IEEE Transactions on Pattern Analysis and Machine Intelligence
Integrated Person Tracking Using Stereo, Color, and Pattern Detection
International Journal of Computer Vision - Special issue on a special section on visual surveillance
Robust Real-Time Periodic Motion Detection, Analysis, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pedestrian Detection in Crowded Scenes
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Simultaneous Estimation of Segmentation and Shape
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Principal Axis-Based Correspondence between Multiple Cameras for People Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Bayesian Detection of Independent Motion in Crowds
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
People detection and tracking using stereo vision and color
Image and Vision Computing
Graphical Models
Stereo Processing by Semiglobal Matching and Mutual Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust pedestrian detection and tracking in crowded scenes
Image and Vision Computing
New Insights into Pedestrian Flow Through Bottlenecks
Transportation Science
Encyclopedia of Complexity and Systems Science - v. 1-10
Encyclopedia of Complexity and Systems Science - v. 1-10
Phase coexistence in congested states of pedestrian dynamics
ACRI'10 Proceedings of the 9th international conference on Cellular automata for research and industry
Multi-cue-based crowd segmentation in stereo vision
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
People detection based on appearance and motion models
AVSS '11 Proceedings of the 2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance
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For the proper understanding and modelling of pedestrian dynamics, reliable empirical data are necessary for analysis and verification. To this end, we have performed a series of experiments with a large number of persons. Such experiments give us the opportunity to selectively analyse parameters independent of undesired influences and adjust them to values seldom seen in field studies. We are developing software for the time-efficient automatic extraction of accurate pedestrian trajectories. Depending on the camera system the software is able to detect and track people on planar or uneven terrain with or without markers. In this paper, we summarise the experiments we have accomplished and the possibilities of our extraction techniques, in particular the newly introduced algorithm of markerless detection in stereo recordings. The markerless detection based on groups of ellipses approximating isolines of the same distance to an overhead stereo camera.