Li, BoQin, HongBing-Yu Chen and Jan Kautz and Tong-Yee Lee and Ming C. Lin2013-10-312013-10-312011978-3-905673-84-5https://doi.org/10.2312/PE/PG/PG2011short/049-054In this paper, we propose a novel approach that transforms discrete volumetric data directly acquired from scanning devices into continuous spline representation with tensor-product regular structure. Our method is achieved through three major steps as follows. First, in order to capture fine features, we construct an as-smooth-as-possible frame field, satisfying a sparse set of directional constraints. Next, a globally smooth parameterization is computed, with iso-parameter curves following the frame field directions. We utilize the parameterization to remesh the data and construct a set of regular-structured volumetric patch layouts, consisting of a small number of volumetric patches while enforcing good feature alignment. Finally, we construct trivariate T-splines on all patches to model geometry and density functions simultaneously. Compared with conventional discrete data, our data-splineconversion results are more efficient and compact, serving as a powerful toolkit with broader application appeal in shape modeling, GPU computing, data reduction, scientific visualization, and physical analysis.Categories and Subject Descriptors (according to ACM CCS): I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling -Curve, surface, solid, and object representations