Feature-preserving triangular geometry images for level-of-detail representation of static and skinned meshes

Abstract

Geometry images resample meshes to represent them as texture for efficient GPU processing by forcing a regular parameterization that often incurs a large amount of distortion. Previous approaches broke the geometry image into multiple rectangular or irregular charts to reduce distortion, but complicated the automatic level of detail one gets from MIP-maps of the geometry image. We introduce triangular-chart geometry images and show this new approach better supports the GPU-side representation and display of skinned dynamic meshes, with support for feature preservation, bounding volumes, and view-dependent level of detail. Triangular charts pack efficiently, simplify the elimination of T-junctions, arise naturally from an edge-collapse simplification base mesh, and layout more flexibly to allow their edges to follow curvilinear mesh features. To support the construction and application of triangular-chart geometry images, this article introduces a new spectral clustering method for feature detection, and new methods for incorporating skinning weights and skinned bounding boxes into the representation. This results in a tenfold improvement in fidelity when compared to quad-chart geometry images.