Sciweavers

CVPR
2001
IEEE

3D Object Recognition from Range Images using Local Feature Histograms

14 years 5 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
Comments (0)