Local Feature Histograms for Object Recognition from Range Images

Bastian Leibe, G√ľnther Hetzel, Paul Levi
University of Stuttgart, Faculty of Computer Science, Technical Report No. 2001/06

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 classi ers 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 ex- tremely fast and can achieve real-time recognition performance.

» Show BibTeX

title={Local feature histograms for object recognition from range images},
author={Leibe, Bastian and Hetzel, G{\"u}nter and Levi, Paul},

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