Classifying Dynamic Objects: An Unsupervised Learning Approach

@inproceedings{Luber2008ClassifyingDO,
  title={Classifying Dynamic Objects: An Unsupervised Learning Approach},
  author={Matthias Luber and Kai Oliver Arras and Christian Plagemann and Wolfram Burgard},
  booktitle={Robotics: Science and Systems},
  year={2008}
}
For robots operating in real-world environments, the ability to deal with dynamic entities such as humans, animals, vehicles, or other robots is of fundamental importance. The variability of dynamic objects, however, is large in general, which makes it hard to manually design suitable models for their appearance and dynamics. In this paper, we present an unsupervised learning approach to this model-building problem. We describe an exemplar-based model for representing the time-varying… CONTINUE READING
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