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Going Further with Point Pair Features

  • Stefan HinterstoisserEmail author
  • Vincent Lepetit
  • Naresh Rajkumar
  • Kurt Konolige
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9907)

Abstract

Point Pair Features is a widely used method to detect 3D objects in point clouds, however they are prone to fail in presence of sensor noise and background clutter. We introduce novel sampling and voting schemes that significantly reduces the influence of clutter and sensor noise. Our experiments show that with our improvements, PPFs become competitive against state-of-the-art methods as it outperforms them on several objects from challenging benchmarks, at a low computational cost.

Supplementary material

Supplementary material 1 (mp4 9942 KB)

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Stefan Hinterstoisser
    • 1
    Email author
  • Vincent Lepetit
    • 2
  • Naresh Rajkumar
    • 1
  • Kurt Konolige
    • 1
  1. 1.GoogleMountain ViewUSA
  2. 2.TU-GrazGrazAustria

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