Overview of recent work on geometry images

Summary form only given. Surfaces in computer graphics are commonly represented using irregular meshes. While such meshes can approximate a given shape using few vertices, their irregularity comes at a price, since most mesh operations require random memory accesses through vertex indices and texture coordinates. Also, filter kernels must handle arbitrary mesh neighborhoods, and techniques like morphing, level-of-detail (LOD) control, and compression are complicated. As an alternative, we have introduced the geometry image representation, which captures shape using a completely regular sampling, i.e. a 2D grid of (x, y, z) values (Guet et al., 2002). The benefits of uniform grids are often taken for granted. Grids allow efficient traversal, random access, convolution, composition, down-sampling, and compression. We briefly review our recent work on constructing geometry images from given input models, and highlight some benefits of this new regular shape representation.