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21
Robust smooth feature extraction from point clouds
 IEEE INTERNATIONAL CONFERENCE ON SHAPE MODELING AND APPLICATIONS
, 2007
"... Defining sharp features in a given 3D model facilitates a better understanding of the surface and aids visualizations, reverse engineering, filtering, simplification, nonphoto realism, reconstruction and other geometric processing applications. We present a robust method that identifies sharp featu ..."
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Cited by 19 (2 self)
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Defining sharp features in a given 3D model facilitates a better understanding of the surface and aids visualizations, reverse engineering, filtering, simplification, nonphoto realism, reconstruction and other geometric processing applications. We present a robust method that identifies sharp features in a point cloud by returning a set of smooth curves aligned along the edges. Our feature extraction is a multistep refinement method that leverages the concept of Robust Moving Least Squares to locally fit surfaces to potential features. Using Newton’s method, we project points to the intersections of multiple surfaces then grow polylines through the projected cloud. After resolving gaps, connecting corners, and relaxing the results, the algorithm returns a set of complete and smooth curves that define the features. We demonstrate the benefits of our method with two applications: surface meshing and pointbased geometry compression.
DuoDecim  A Structure for Point Scan Compression and Rendering
, 2005
"... In this paper we present a compression scheme for large point scans including perpoint normals. For the encoding of such scans we introduce a particular type of closest sphere packing grids, the hexagonal close packing (HCP). HCP grids provide a structure for an optimal packing of 3D space, and for ..."
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Cited by 16 (2 self)
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In this paper we present a compression scheme for large point scans including perpoint normals. For the encoding of such scans we introduce a particular type of closest sphere packing grids, the hexagonal close packing (HCP). HCP grids provide a structure for an optimal packing of 3D space, and for a given sampling error they result in a minimal number of cells if geometry is sampled into these grids. To compress the data, we extract linear sequences (runs) of filled cells in HCP grids. The problem of determining optimal runs is turned into a graph theoretical one. Point positions and normals in these runs are incrementally encoded. At a grid spacing close to the point sampling distance, the compression scheme only requires slightly more than 3 bits per point position. Incrementally encoded perpoint normals are quantized at high fidelity using only 5 bits per normal (see Figure 1). The compressed data stream can be decoded in the graphics processing unit (GPU). Decoded point positions are saved in graphics memory, and they are then used on the GPU again to render point primitives. In this way we render gigantic point scans from their compressed representation in local GPU memory at interactive frame rates (see Figure 2).
A Generic Scheme for Progressive Point Cloud Coding
"... In this paper, we propose a generic point cloud encoder that provides a unified framework for compressing different attributes of point samples corresponding to 3D objects with arbitrary topology. In the proposed scheme, the coding process is led by an iterative octree cell subdivision of the objec ..."
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Cited by 10 (1 self)
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In this paper, we propose a generic point cloud encoder that provides a unified framework for compressing different attributes of point samples corresponding to 3D objects with arbitrary topology. In the proposed scheme, the coding process is led by an iterative octree cell subdivision of the object space. At each level of subdivision, positions of point samples are approximated by the geometry centers of all treefront cells while normals and colors are approximated by their statistical average within each of treefront cells. With this framework, we employ attributedependent encoding techniques to exploit different characteristics of various attributes. All of these have led to significant improvement in the ratedistortion (RD) performance and a computational advantage over the state of the art. Furthermore, given sufficient levels of octree expansion, normal space partitioning and resolution of color quantization, the proposed point cloud encoder can be potentially used for lossless coding of 3D point clouds.
Hardware rendering of 3D geometry with elevation maps
 In Proc. International Conference on Shape Modeling and Applications
, 2006
"... We present a generic framework for realtime rendering of 3D surfaces. We use the common elevation map primitive, by which a given surface is decomposed into a set of patches. Each patch is parameterized as an elevation map over a planar domain and resampled on a regular grid. While current hardware ..."
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Cited by 4 (2 self)
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We present a generic framework for realtime rendering of 3D surfaces. We use the common elevation map primitive, by which a given surface is decomposed into a set of patches. Each patch is parameterized as an elevation map over a planar domain and resampled on a regular grid. While current hardware accelerated rendering approaches require conversion of this representation back into a triangle mesh or point set, we propose to render the elevation maps directly in a hardware accelerated environment. We use one base data set to render each patch in the common vertex and fragment shader pipeline. We implement meshor pointbased rendering by using a base mesh or a base point set respectively. This provides the basis for the underlying primitive for the final rendering. We show the benefits of this method for splat rendering by replacing attribute blending through a simplified and fast attribute interpolation. This results in rendering acceleration as well as an improvement in visual quality when compared to previous approaches. 1
Point set compression through BSP quantization
 In Proceedings of the Brazilian Symposium on Computer Graphics and Image Processing
, 2006
"... Abstract. This work introduces a new compression scheme for point sets. This scheme relies on an adaptive binary space partition (BSP) which takes into account the geometric structure of the point set. This choice introduces geometrical rather than combinatorial information in the compression scheme ..."
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Cited by 2 (1 self)
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Abstract. This work introduces a new compression scheme for point sets. This scheme relies on an adaptive binary space partition (BSP) which takes into account the geometric structure of the point set. This choice introduces geometrical rather than combinatorial information in the compression scheme. In order to effectively improve the final compression ratio, this partition is encoded in a progressive manner, decreasing the number of bits used for the quantisation at each subdivision. This strategy distributes the extra cost of the geometry encoding onto the maximal number of points, compressing in average 15 % more than previous techniques.
Compression of Textured Surfaces Represented as Surfel Sets
, 2006
"... A method for lossy compression of genus0 surfaces is presented. Geometry, texture and other surface attributes are incorporated in a unified manner. The input surfaces are represented by surfels (surface elements), i.e., by a set of disks with attributes. Each surfel, with its attribute vector, is ..."
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Cited by 2 (2 self)
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A method for lossy compression of genus0 surfaces is presented. Geometry, texture and other surface attributes are incorporated in a unified manner. The input surfaces are represented by surfels (surface elements), i.e., by a set of disks with attributes. Each surfel, with its attribute vector, is optimally mapped onto a sphere in the sense of geodesic distance preservation. The resulting spherical vectorvalued function is resampled. Its components are decorrelated by the KarhunenLoève transform, represented by spherical wavelets and encoded using the zerotree algorithm. Methods for geodesic distance computation on surfelbased surfaces are considered. A novel efficient approach to dense surface flattening/mapping, using rectangular distance matrices, is employed. The distance between each surfel and a set of keysurfels is optimally preserved, leading to greatly improved resolution and eliminating the need for interpolation, that complicates and slows down existing surface unfolding methods. Experimental surfelbased surface compression results demonstrate successful compression at very low bit rates.
ImageBased Surface Compression
, 2008
"... We present a generic framework for compression of densely sampled 3D surfaces in order to satisfy the increasing demand for storing large amounts of 3D content. We decompose a given surface into patches that are parameterized as elevation maps over planar domains and resampled on regular grids. The ..."
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Cited by 2 (0 self)
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We present a generic framework for compression of densely sampled 3D surfaces in order to satisfy the increasing demand for storing large amounts of 3D content. We decompose a given surface into patches that are parameterized as elevation maps over planar domains and resampled on regular grids. The resulting shaped images are encoded using a stateoftheart wavelet image coder. We show that our method is not only applicable to meshand pointbased geometry, but also outperforms current surface encoders for both primitives.
Processing of textured surfaces represented as surfel sets: Representation, compression and geodesic paths
 in: Proceedings of the IEEE International Conference on Image Processing, 2005
"... A method for representation and lossy compression of textured surfaces is presented. The input surfaces are represented by surfels (surface elements), i.e., by a set of colored, oriented, and sized disks. The position and texture of each surfel are mapped onto a sphere. The mapping is optimized ..."
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Cited by 1 (1 self)
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A method for representation and lossy compression of textured surfaces is presented. The input surfaces are represented by surfels (surface elements), i.e., by a set of colored, oriented, and sized disks. The position and texture of each surfel are mapped onto a sphere. The mapping is optimized for preservation of geodesic distances. The components of the resulting spherical vectorvalued function are decorrelated by the KarhunenLoève transform and represented by spherical wavelets. Successful representation and reconstruction is demonstrated. Methods for geodesic distance computation on surfaces represented by surfels are presented. 1.
1A Generic Scheme for Progressive Point Cloud Coding
"... All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
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All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.