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Recognition and Localization Techniques

  • Minsoo Suk
  • Suchendra M. Bhandarkar
Part of the Computer Science Workbench book series (WORKBENCH)

Abstract

Having obtained a feature-level description of the scene, the next step is matching these features with those computed from the internal representation of the object models. The purpose of the matching process is two-fold—first, to label the features in the scene as an instance of an object model and, second, to determine the position and orientation of the object in the scene with respect to a reference coordinate frame. The process of labeling scene features as having arisen from a particular object model is referred to as recognition, whereas determining the position and orientation of an object in the scene is referred to as localization. In fact, most matching techniques treat recognition and localization as two inseparable issues of the same overall problem, to the extent that the term recognition is often used to denote both recognition and localization.

Keywords

Object Model Hash Table Unary Constraint Surface Patch Binary Constraint 
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 Tokyo 1992

Authors and Affiliations

  • Minsoo Suk
    • 1
  • Suchendra M. Bhandarkar
    • 2
  1. 1.Department of Electrical and Computer EngineeringSyracuse UniversitySyracuseUSA
  2. 2.Department of Computer ScienceUniversity of GeorgiaAthensUSA

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