Sharpening and Sparsifying with Surface Hessians
SessionMesh Processing Unleashed
DescriptionThe L1 Hessian energy measures the norm of the Hessian of a function on a surface (and NOT the squared norm, as is common with many geometry applications that employ L2). Its minimizers tend to be locally linear with a sparse set of curved ridges. We introduce a fully-intrinsic discretization of this energy for triangle meshes and show that it can be optimized using off-the-shelf conic program solvers. We apply it to stylization, denoising, interpolation, hole-filling, and segmentation tasks. Our L1 approach exhibits multiple important differences from its more-familiar L2 counterpart: it preserves ridge-like features in the input, it naturally incorporates a flatness prior for reconstruction, and, at its extreme, it distills its input to an abstract, angular form.
Event Type
Technical Papers
TimeThursday, 5 December 20243:27pm - 3:41pm JST
LocationHall B5 (1), B Block, Level 5
