Abstract:
This paper develops a new class of parameterized models based on the linear interpolation of two parameterized shapes along their main axes, using a blending function. Th...Show MoreMetadata
Abstract:
This paper develops a new class of parameterized models based on the linear interpolation of two parameterized shapes along their main axes, using a blending function. This blending function specifies the relative contribution of each component shape on the resulting blended shape. The resulting blended shape can have aspects of each of the component shapes. Using a small number of additional parameters, blending extends the coverage of shape primitives while also providing abstraction of shape. In particular, it offers the ability to construct shapes whose genus can change. Blended models are incorporated into a physics-based shape estimation framework which uses dynamic deformable models. Finally, we present experiments involving the extraction of complex shapes from range data including examples of dynamic genus change.
Published in: IEEE Transactions on Pattern Analysis and Machine Intelligence ( Volume: 18, Issue: 4, April 1996)
DOI: 10.1109/34.491626