Name
Abstract | ||
|---|---|---|
We present a new method for computing the shape similarity between 3D polygonal models using an information- theoretic viewpoint selection framework. Given a 3D model, a sphere of viewpoints surrounding this model is used to obtain its shape signature from the mutual information of each viewpoint. This signature represents the essence of the shape from a view-based approach. Then, in order to quantify the dissimilarity between two models, their mutual information spheres are registered by minimizing the L2 distance between them. Several experiments show the discrimination capabilities of our approach and its potential suitability for object recognition. |
Year | Venue | Field |
|---|---|---|
2007 | Eurographics (Short Papers) | Computer vision,Active shape model,Polygon,Pattern recognition,Viewpoints,View based,Variation of information,Mutual information,SPHERES,Artificial intelligence,Mathematics,Cognitive neuroscience of visual object recognition |
DocType | Citations | PageRank |
Conference | 3 | 0.39 |
References | Authors | |
7 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Francisco González García | 1 | 3 | 0.39 |
| Miquel Feixas | 2 | 637 | 45.61 |
| Mateu Sbert | 3 | 1108 | 123.95 |