SMRFI: Shape Matching via Registration of Feature Images

Principal Investigator: Ghassan Hamarneh
MSc Student: Lisa Tang

We perform shape matching by transforming the problem into an image registration task. At each vertex on the shape, we calculate a shape feature and encode this feature as image intensity at appropriate positions in the image domain. Calculating multiple features at each vertex and encoding them into the image domain results in a vector-valued feature image. Establishing point correspondence between two shapes is thereafter treated as a registration problem of two vector-valued feature images. With this shape representation, various existing image registration strategies can now be easily applied. These include the use of a scale-space approach to diffuse the shape features, a coarse-to-fine registration scheme, and various deformable registration algorithms.


Lisa Tang and Ghassan Hamarneh. SMRFI: Shape Matching via Registration of Vector-Valued Feature Images. In IEEE Computer Vision and Pattern Recognition (IEEE CVPR), pages 8 pages (accepted), 2008. [PDF] [POSTER]


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