Combining LiDAR space clustering and convolutional neural networks for pedestrian detection

@article{Matti2017CombiningLS,
  title={Combining LiDAR space clustering and convolutional neural networks for pedestrian detection},
  author={Damien Matti and H. K. Ekenel and J. Thiran},
  journal={2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)},
  year={2017},
  pages={1-6}
}
  • Damien Matti, H. K. Ekenel, J. Thiran
  • Published 2017
  • Computer Science
  • 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)
  • Pedestrian detection is an important component for safety of autonomous vehicles, as well as for traffic and street surveillance. [...] Key Method In the proposed approach, LiDAR data is utilized to generate region proposals by processing the three dimensional point cloud that it provides. These candidate regions are then further processed by a state-of-the-art CNN classifier that we have fine-tuned for pedestrian detection. We have extensively evaluated the proposed detection process on the KITTI dataset. The…Expand Abstract
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