Robust Pose Estimation Using the SwissRanger SR-3000 Camera

  • Sigurjón Árni Guðmundsson
  • Rasmus Larsen
  • Bjarne K. Ersbøll
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4522)

Abstract

In this paper a robust method is presented to classify and estimate an objects pose from a real time range image and a low dimensional model. The model is made from a range image training set which is reduced dimensionally by a nonlinear manifold learning method named Local Linear Embedding (LLE). New range images are then projected to this model giving the low dimensional coordinates of the object pose in an efficient manner. The range images are acquired by a state of the art SwissRanger SR-3000 camera making the projection process work in real-time.

Keywords

Range Image Training Point Locally Linear Embedding Nonlinear Manifold Intrinsic Dimensionality 
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 Berlin Heidelberg 2007

Authors and Affiliations

  • Sigurjón Árni Guðmundsson
    • 1
  • Rasmus Larsen
    • 1
  • Bjarne K. Ersbøll
    • 1
  1. 1.Technical University of Denmark, Informatics and Mathematical Modelling, Building 321, Richard Petersens Plads, DTU DK-2800 Kgs. Lyngby 

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