3D object recognition from range images using local feature histograms
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Авторы: Hetzel G.
Leibe B.
Levi P.
Schiele B.
Библиографическая ссылка:Hetzel G., Leibe B., Levi P., Schiele B. 3D object recognition from range images using local feature histograms // IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Kauai, USA, 8-14 December, 2001. IEEE Computer Society, 2001. P. 394-399.
Аннотация:

The 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.

Ключевые слова: Без рубрики, Трехмерное моделирование объекта, Гистограмма локальных особенностей
Код:HetzelLLS 01
Последняя правка: 17.10.2011 20:25:12