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3DPVT
2006
IEEE

Shape Measure for Identifying Perceptually Informative Parts of 3D Objects

8 years 11 months ago
Shape Measure for Identifying Perceptually Informative Parts of 3D Objects
We propose a mathematical approach for quantifying shape complexity of 3D surfaces based on perceptual principles of visual saliency. Our curvature variation measure (CVM), as a 3D feature, combines surface curvature and information theory by leveraging bandwidth-optimized kernel density estimators. Using a part decomposition algorithm for digitized 3D objects, represented as triangle meshes, we apply our shape measure to transform the low level mesh representation into a perceptually informative form. Further, we analyze the effects of noise, sensitivity to digitization, occlusions, and descriptiveness to demonstrate our shape measure on laser-scanned real world 3D objects.
Sreenivas R. Sukumar, David Page, Andrei V. Gribok
Added 10 Jun 2010
Updated 10 Jun 2010
Type Conference
Year 2006
Where 3DPVT
Authors Sreenivas R. Sukumar, David Page, Andrei V. Gribok, Andreas Koschan, Mongi A. Abidi
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