Object tracking via the probability-based segmentation using laser range images

@article{Lee2010ObjectTV,
  title={Object tracking via the probability-based segmentation using laser range images},
  author={Yung-Chou Lee and Tesheng Hsiao},
  journal={2010 IEEE Intelligent Vehicles Symposium},
  year={2010},
  pages={197-202}
}
In this paper, a probability-based segmentation approach is presented for object tracking. The proposed approach uses the Dirichlet process mixture model to describe the probabilistic distribution of observations in a single scan of a laserscanner. Then the number of segments is inferred from the observations by the Gibbs sampling method. Moreover each segment is classified into one of the three predefined classes such that most of non-vehicle-like objects on the roadsides can be filtered out… CONTINUE READING
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