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Local Feature Histograms for Object Recognition from Range Images

Authors
  • Leibe, B.
  • Hetzel, G.
  • Levi, P.
Publication Date
Aug 23, 2001
Source
Universität Stuttgart, Fakultät 5, Germany, Computer Science Archive
Keywords
Language
English
License
Unknown
External links

Abstract

In this paper, we explore the use of local feature histograms for view-based recognition of free-form objects from range images. Our approach uses a set of local features that are easy to calculate and robust to partial occlusions. By combining them in a multidimensional histogram, we can obtain highly discriminative classifiers without having to solve a segmentation problem. The system achieves above 91% recognition accuracy on a database of almost 2000 full-sphere views of 30 free-form objects, with only minimal space requirements. In addition, since it only requires the calculation of very simple features, it is extremely fast and can achieve real-time recognition performance.

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