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2001
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3D Object Recognition from Range Images using Local Feature Histograms

9 years 6 months ago
3D Object Recognition from Range Images using Local Feature Histograms
This paper explores a view-based approach to recognize free-form objects in range images. We are using a set of local features that are easy to calculate and robust to partial occlusions. By combining those features in a multidimensional histogram, we can obtain highly discriminant classifiers without the need for segmentation. Recognition is performed using either histogram matching or a probabilistic recognition algorithm. We compare the performance of both methods in the presence of occlusions and test the system on a database of almost 2000 full-sphere views of 30 free-form objects. The system achieves a recognition accuracy above 93% on ideal images, and of 89% with 20% occlusion.
Bastian Leibe, Bernt Schiele, Günter Hetzel,
Added 12 Oct 2009
Updated 12 Oct 2009
Type Conference
Year 2001
Where CVPR
Authors Bastian Leibe, Bernt Schiele, Günter Hetzel, Paul Levi
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