Skeletal representations of orthogonal shapes

In this paper we present two skeletal representations applied to orthogonal shapes of R^n : the cube axis and a family of skeletal representations provided by the scale cube axis. Orthogonal shapes are a subset of polytopes, where the hyperplanes of the bounding facets are restricted to be axis aligned. Both skeletal representations rely on the L∞ metric and are proven to be homotopically equivalent to its shape. The resulting skeleton is composed of n − 1 dimensional facets. We also provide an efficient and robust algorithm to compute the scale cube axis in the plane and compare the resulting skeleton with other skeletal representations.Postprint (published version

Locally-adaptive texture compression

Current schemes for texture compression fail to exploit spatial coherence in an adaptive manner due to the strict efficiency constraints imposed by GPU-based, fragment-level decompression. In this paper we present a texture compression framework for quasi-lossless, locally-adaptive compression of graphics data. Key elements include a Hilbert scan to maximize spatial coherence, efficient encoding of homogeneous image regions through arbitrarilysized texel runs, a cumulative run-length encoding supporting fast random-access, and a compression algorithm suitable for fixed-rate and variable-rate encoding. Our scheme can be easily integrated into the rasterization pipeline of current programmable graphics hardware allowing real-time GPU decompression. We show that our scheme clearly outperforms competing approaches such as S3TC DXT1 on a large class of images with some degree of spatial coherence. Unlike other proprietary formats, our scheme is suitable for compression of any graphics data including color maps, shadow maps and relief maps. We have observed compression rates of up to 12:1, with minimal or no loss in visual quality and a small impact on rendering time.Peer ReviewedPostprint (published version

Locally-adaptive texture compression

Current schemes for texture compression fail to exploit spatial coherence in an adaptive manner due to the strict efficiency constraints imposed by GPU-based, fragment-level decompression. In this paper we present a texture compression framework for quasi-lossless, locally-adaptive compression of graphics data. Key elements include a Hilbert scan to maximize spatial coherence, efficient encoding of homogeneous image regions through arbitrarilysized texel runs, a cumulative run-length encoding supporting fast random-access, and a compression algorithm suitable for fixed-rate and variable-rate encoding. Our scheme can be easily integrated into the rasterization pipeline of current programmable graphics hardware allowing real-time GPU decompression. We show that our scheme clearly outperforms competing approaches such as S3TC DXT1 on a large class of images with some degree of spatial coherence. Unlike other proprietary formats, our scheme is suitable for compression of any graphics data including color maps, shadow maps and relief maps. We have observed compression rates of up to 12:1, with minimal or no loss in visual quality and a small impact on rendering time.Peer Reviewe

Locally-adaptive texture compression

Current schemes for texture compression fail to exploit spatial coherence in an adaptive manner due to the strict efficiency constraints imposed by GPU-based, fragment-level decompression. In this paper we present a texture compression framework for quasi-lossless, locally-adaptive compression of graphics data. Key elements include a Hilbert scan to maximize spatial coherence, efficient encoding of homogeneous image regions through arbitrarilysized texel runs, a cumulative run-length encoding supporting fast random-access, and a compression algorithm suitable for fixed-rate and variable-rate encoding. Our scheme can be easily integrated into the rasterization pipeline of current programmable graphics hardware allowing real-time GPU decompression. We show that our scheme clearly outperforms competing approaches such as S3TC DXT1 on a large class of images with some degree of spatial coherence. Unlike other proprietary formats, our scheme is suitable for compression of any graphics data including color maps, shadow maps and relief maps. We have observed compression rates of up to 12:1, with minimal or no loss in visual quality and a small impact on rendering time.Peer Reviewe

The oxidation of NdFeB alloys

Available from British Library Document Supply Centre-DSC:DXN053918 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

Central Laser Facility, Rutherford Appleton Laboratory Annual report 1999/2000

SIGLEAvailable from British Library Document Supply Centre-DSC:8715.1804(2000-034) / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Skeletal representations of orthogonal shapes

In this paper we present two skeletal representations applied to orthogonal shapes of R^n : the cube axis and a family of skeletal representations provided by the scale cube axis. Orthogonal shapes are a subset of polytopes, where the hyperplanes of the bounding facets are restricted to be axis aligned. Both skeletal representations rely on the L∞ metric and are proven to be homotopically equivalent to its shape. The resulting skeleton is composed of n − 1 dimensional facets. We also provide an efficient and robust algorithm to compute the scale cube axis in the plane and compare the resulting skeleton with other skeletal representations

Skeletal representations of orthogonal shapes

In this paper we present two skeletal representations applied to orthogonal shapes of R^n : the cube axis and a family of skeletal representations provided by the scale cube axis. Orthogonal shapes are a subset of polytopes, where the hyperplanes of the bounding facets are restricted to be axis aligned. Both skeletal representations rely on the L∞ metric and are proven to be homotopically equivalent to its shape. The resulting skeleton is composed of n − 1 dimensional facets. We also provide an efficient and robust algorithm to compute the scale cube axis in the plane and compare the resulting skeleton with other skeletal representations

Skeleton computation of orthogonal polyhedra

Skeletons are powerful geometric abstractions that provide useful representations for a number of geometric operations. The straight skeleton has a lower combinatorial complexity compared with the medial axis. Moreover, while the medial axis of a polyhedron is composed of quadric surfaces the straight skeleton just consist of planar faces. Although there exist several methods to compute the straight skeleton of a polygon, the straight skeleton of polyhedra has been paid much less attention. We require to compute the skeleton of very large datasets storing orthogonal polyhedra. Furthermore, we need to treat geometric degeneracies that usually arise when dealing with orthogonal polyhedra. We present a new approach so as to robustly compute the straight skeleton of orthogonal polyhedra. We follow a geometric technique that works directly with the boundary of an orthogonal polyhedron. Our approach is output sensitive with respect to the number of vertices of the skeleton and solves geometric degeneracies. Unlike the existing straight skeleton algorithms that shrink the object boundary to obtain the skeleton, our algorithm relies on the plane sweep paradigm. The resulting skeleton is only composed of axis-aligned and 45 rotated planar faces and edges.Peer Reviewe

Skeletal representations of orthogonal shapes

Orthogonal shapes are polygons orpolyhedra enclosed byaxis-aligned edges orfaces, respectively. Inthis paper wepresent two skeletal representatio nsoforthogonal shapes: the cube skeleton and a family ofskeletal represe ntations provided bythe scale cube skeleton. Both skeletal represe ntations rely onthe L1 metric. Weshow that the cube skeleton is homotopically equivalent to its original shape,reduces its dimension,and it is composed of line segments orplanar polygons with restricted orientation. We also present analgorithm to compute the scale cube skeleton oforthogonal polygons and compare the presented skeletons with other skeletal represe ntations