Pedestrian Detection and Tracking Using Three-Dimensional LADAR Data

  • Luis E. Navarro-Serment
  • Christoph Mertz
  • Martial Hebert
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 62)


The approach investigated in this work employs three-dimensional LADAR measurements to detect and track pedestrians over time. The sensor is employed on a moving vehicle. The algorithm quickly detects the objects which have the potential of being humans using a subset of these points, and then classifies each object using statistical pattern recognition techniques. The algorithm uses geometric and motion features to recognize human signatures. The perceptual capabilities described form the basis for safe and robust navigation in autonomous vehicles, necessary to safeguard pedestrians operating in the vicinity of a moving robotic vehicle.


Point Cloud Autonomous Vehicle Human Detection Pedestrian Detection Unmanned Ground Vehicle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Luis E. Navarro-Serment
    • 1
  • Christoph Mertz
    • 1
  • Martial Hebert
    • 1
  1. 1.The Robotics InstituteCarnegie Mellon UniversityPittsburgh

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