Flexible Painting-Based Volume Classification Using Ellipsoid Gaussian Transfer Function
The paper focuses on appearance and spatial property-based volume classification with a painting interface. Two key problems exist, i.e., effectively propagating user-given painting to the entire volume and intuitively controlling the roles of appearance and spatial properties, which are not well solved in existing painting-based transfer function specification methods. The present paper formulates painting propagation as a function interpolation problem in a high-dimensional affine space and solves it effectively using Gaussian radial basis functions. For the second problem, the present work presents a two-step approach, which first propagates the user-given painting to the entire volume using appearance- and spatial-property-dominated feature vectors, and then combines the painting propagation results using an ellipsoid Gaussian transfer function (ETF) for volume classification. The user can intuitively manipulate ETF using system-provided widgets. The effectiveness of the proposed method has been verified on several datasets.
Volume rendering Transfer function Painting interface Ellipsoid Gaussian transfer function (ETF) Gaussian radial basis functions (GRBFs)
Yuetong Luo Jinsheng Chen Hanbin Wang Deqing Qu Jie Wang Wenmin Tan
VCC Division, School of Computer & Information, Hefei University of Technology
国内会议
北京
英文
1-7
2011-11-04（万方平台首次上网日期，不代表论文的发表时间）