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Improved feature descriptors for 3-D surface matching (2007) Luke J Skelly and Stan Sclaroff |
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| Abstract: Our interest is in data registration, object recognition, and object tracking using 3D point clouds. There are three steps to our feature matching system: detection, description, and matching. Our focus in this paper is on the feature description step. We describe new rotation invariant 3D feature descriptors that utilize ideas from the well-known 2D SIFT descriptor for image features. We experiment with a variety of synthetic and real data to show how well our newly developed descriptors perform relative to a commonly used 3D descriptor, spin images. Our results show that our descriptors are more distinctive than spin images, while remaining rotation and translation invariant. The improvement in performance in comparison to spin images is most evident when an object has features that are mirror images of each other, due to symmetry. | |||
| Published in: Proc. SPIE Conf. on Two- and Three-Dimensional Methods for Inspection and Metrology V, Vol. SPIE 6762, 2007. | |||
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