Automatic feature tracking is widely used for the analysis of timedependent data. If the features exhibit splitting behavior, it is best characterized by tree-like tracks. For a large number of time steps, each with n...
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We present a new particle-based surface representation with which a user can interactively sculpt free-form surfaces. The particles maintain mesh connectivity and operate under rules that lead them to form triangulati...
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ISBN:
(纸本)0201485605
We present a new particle-based surface representation with which a user can interactively sculpt free-form surfaces. The particles maintain mesh connectivity and operate under rules that lead them to form triangulations with properties that make them suitable for use in subdivision. A user interactively guides the particles, which we call skin, to grow over a given collection of polyhedral elements (or skeletons), yielding a smooth surface (through subdivision) that approximates the underlying skeletal shapes. Skin resembles blobby modeling in the constructive approach to modeling it supports, but allows a richer vocabulary of skeleton shapes, supports sharp creases where desired, and provides a convenient mechanism for adding multiresolution surface detail. Copyright ACM 1999.
An important task in archaeological research is the comparison of painted motifs on ancient vessels and the analysis of their painting style. Ideally, the pottery objects are available as scanned 3D models, from which...
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This paper describes the design and the implementation of a distributed object repository that offers cultural heritage experts and practitioners a working platform to access, use, share and modify digital content. Th...
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Image segmentation (or masking) finds a very useful use case within 3D reconstruction of cultural heritage objects. The 3D reconstructions can be accelerated, reconstructing the object without any background noise. Co...
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We describe some issues in designing and building educational Java applets for an introductory computergraphics course. The design problem involves balancing educational goals of building intuition about fundamental ...
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We present dense medial descriptors, a new technique which generalizes the well-known medial axes to encode and manipulate whole 2D grayvalue images, rather than binary shapes. To compute our descriptors, we first red...
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ISBN:
(纸本)9789898565471
We present dense medial descriptors, a new technique which generalizes the well-known medial axes to encode and manipulate whole 2D grayvalue images, rather than binary shapes. To compute our descriptors, we first reduce an image to a set of threshold-sets in luminance space. Next, we compute a simplified representation of each threshold-set using a noise-resistant medial axis transform. Finally, we use these medial axis transforms to perform a range of operations on the input image, from perfect reconstruction to segmentation, simplification, and artistic effects. Our pipeline can robustly handle any 2D grayscale image, is easy to use, and allows an efficient CPU or GPU-based implementation. We demonstrate our dense medial descriptors with several image-processing applications.
In this paper we present a compression scheme for large point scans including per-point normals. For the encoding of such scans we introduce a particular type of closest sphere packing grids, the hexagonal close packi...
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In this paper we present a compression scheme for large point scans including per-point 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 per-point normals are quantized at high fidelity using only 5 bits per normal. 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.
Dimension reduction is commonly defined as the process of mapping high-dimensional data to a lower-dimensional embedding. Applications of dimension reduction include, but are not limited to, filtering, compression, re...
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ISBN:
(纸本)9783939897460
Dimension reduction is commonly defined as the process of mapping high-dimensional data to a lower-dimensional embedding. Applications of dimension reduction include, but are not limited to, filtering, compression, regression, classification, feature analysis, and visualization. We review methods that compute a point-based visual representation of high-dimensional data sets to aid in exploratory data analysis. The aim is not to be exhaustive but to provide an overview of basic approaches, as well as to review select state-of-the-art methods. Our survey paper is an introduction to dimension reduction from a visualization point of view. Subsequently, a comparison of state-of-the-art methods outlines relations and shared research foci.
We present the Bio Scene Graph (BioSG) for visualization of biomolecular structures based on the scene graph system OpenSG. The hierarchical model of primary, secondary and tertiary structures of molecules used in the...
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