Part-based data-driven shape interpolation

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2018
Aydınlılar, Melike
An active problem in digital geometry processing is shape interpolation which aims to generate a continuous sequence of in-betweens for a given source and target shape. Unlike traditional approaches that interpolate source and target shapes in isolation, recent data-driven approaches utilize multiple interpolations through intermediate database shapes, and consequently perform better at the expense of a database requirement. In contrast to the existing data-driven approaches that consider intermediate shapes as full inseparable entities, our novel data-driven method treats the shapes as separable rigid parts. In particular, we interpolate rigid parts over different intermediate shapes and merge them all in the end, which brings more flexibility and variety than the existing ways of interpolating the full shape as a whole over one fixed set of intermediates. To be able to proceed consistently over different sets of intermediate shapes, we construct a unified framework based on parametric curves. We demonstrate visually appealing and natural shape interpolation results in comparison with two other techniques. As a side contribution, we provide a public articulated hand dataset with fixed connectivity, which can be used in the evaluation of other shape interpolation methods. Our code and executables are also publicly available.

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Citation Formats
M. Aydınlılar, “Part-based data-driven shape interpolation,” M.S. - Master of Science, Middle East Technical University, 2018.