Abstract
Spin image is a powerful shape descriptor, useful in a point set or surface registration. However, the usage of spin images is hampered by issues such as sensitivity to noise and sampling rate and time-consuming matching process. We propose a novel spin-image-based local surface descriptor named spin contour to alleviate these problems. This descriptor is not an image but a 2-D point set. Comparisons show that the spin contour is robust to noise and sampling differences. The matching time is also improved over spin images.
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