Distinctive Feature Selection
نویسندگان
چکیده
We proposed a new method to select distinctive features for 3D shape. This approach combines the techniques of neighborhood preserved dimensionality reduction algorithm with clustering method. Based on experimental result, it turns out that the proposed method has better distinctive feature retrieval performance in low dimensional mapping. Using our method, we achieved a reasonably accuracy in 3D shape classification through experiments.
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