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Improving SIFT-Based Object Recognition for Robot Applications

  • Patricio Loncomilla
  • Javier Ruiz-del-Solar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)

Abstract

In this article we proposed an improved SIFT-based object recognition methodology for robot applications. This methodology is employed for implementing a robot-head detection system, which is the main component of a robot gaze direction determination system. Gaze direction determination of robots is an important ability to be developed. It can be used for enhancing cooperative and competitive skills in situations where the robots interacting abilities are important, as for example, robot soccer. Experimental results of the implemented robot-head detection system are presented.

Keywords

Interest Point Affine Transformation Local Extremum Scale Invariant Feature Transform Robot Soccer 
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 2005

Authors and Affiliations

  • Patricio Loncomilla
    • 1
    • 2
  • Javier Ruiz-del-Solar
    • 1
    • 2
  1. 1.Department of Electrical EngineeringUniversidad de Chile 
  2. 2.Center for Web Research, Department of Computer ScienceUniversidad de Chile 

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