Distance ranked connectivity compression of triangle meshes

We present a new, single-rate method for compressing the connectivity information of a 2-manifold triangle mesh with or without boundary. Traditional compression schemes interleave geometry and connectivity coding, and are thus unable to utilise information from vertices (mesh regions) they have not yet processed. With the advent of competitive point cloud compression schemes, it has become feasible to develop separate connectivity encoding schemes which can exploit complete, global vertex position information to improve performance. Our scheme demonstrates the utility of this separation of vertex and connectivity coding. By traversing the mesh edges in a consistent breadth-first fashion, and using global vertex information, we can predict the position of the vertex which completes the unprocessed triangle attached to a given edge. We then rank the vertices in the neighbourhood of this predicted position by their Euclidean distance. The distance rank of the correct closing vertex is stored. Typically, these rank values are small, and the sequence of rank values thus possesses low entropy and compresses very well. The paper details the algorithm as well as the predictors we have tested. Results indicate improvement on the current best valence-based schemes for many common mesh classes

Topology Alteration for Virtual Sculpting using Spatial Deformation

Virtual Sculpting enables the creation of computer models by emulating traditional sculpting. It can be implemented using spatial deformation, an interactive versatile modelling technique. Unfortunately, spatial deformation is limited to topology preserving warping. This is overcome by space-time objects, a variant of spatial deformation, which alters topology by extruding an object into 4-D, deforming the 4-D object and extracting a topologically altered object. However, they are specifically targeted to animation. In this paper, we adapt space-time objects to interactive modelling by: employing a tetrahedral rather than parallelepiped representation; exploiting coherence during the constant projection into four dimensions; and limiting projection to the portions of an object undergoing topology changes and thereby producing simpler triangulations of undeformed regions. Each of these adaptations is discussed in the context of the space-time object stages: extrusion, deformation and extraction. We also present preliminary results demonstrating the efficiency of our improvements

A Survey of Spatial Deformation from a User-Centered Perspective

The spatial deformation methods are a family of modeling and animation techniques for indirectly reshaping an object by warping the surrounding space, with results that are similar to molding a highly malleable substance. They have the virtue of being computationally efficient (and hence interactive) and applicable to a variety of object representations. In this paper we survey the state of the art in spatial deformation. Since manipulating ambient space directly is infeasible, deformations are controlled by tools of varying dimension - points, curves, surfaces and volumes - and it is on this basis that we classify them. Unlike previous surveys that concentrate on providing a single underlying mathematical formalism, we use the user-centered criteria of versatility, ease of use, efficiency and correctness to compare techniques

Fast in-place binning of laser range-scanned point sets

Laser range scanning is commonly used in cultural heritage to create digital models of real-world artefacts. A large scanning campaign can produce billions of point samples — too many to be manipulated in memory on most computers. It is thus necessary to spatially partition the data so that it can be processed in bins or slices. We introduce a novel compression mechanism that exploits spatial coherence in the data to allow the bins to be computed with only 1.01 bytes of I/O traffic for each byte of input, compared to 2 or more for previous schemes. Additionally, the bins are loaded from the original files for processing rather than from a sorted copy, thus minimising disk space requirements. We demonstrate that our method yields performance improvements in a typical point-processing task, while also using little memory and guaranteeing an upper bound on the number of samples held in-core

Moving Least-Squares Reconstruction of Large Models with GPUs

Modern laser range scanning campaigns produce extremely large point clouds, and reconstructing a triangulated surface thus requires both out-of-core techniques and significant computational power. We present a GPU-accelerated implementation of the Moving Least Squares (MLS) surface reconstruction technique. While several previous out-of-core approaches use a sweep-plane approach, we subdivide the space into cubic regions that are processed independently. This independence allows the algorithm to be parallelized using multiple GPUs, either in a single machine or a cluster. It also allows data sets with billions of point samples to be processed on a standard desktop PC. We show that our implementation is an order of magnitude faster than a CPU-based implementation when using a single GPU, and scales well to 8 GPUs

Terrain Sketching

Procedural methods for terrain synthesis are capable of creating realistic depictions of heightfield terrains with little user intervention. However, users often do wish to intervene in controlling the placement and shape of landforms, but without sacrificing realism. In this paper, we present a sketching interface to procedural terrain generation. This system enables users to draw the silhouette, spine and bounding curves of both extruding (hills and mountains) and embedding landforms (river courses and canyons). Terrain is interactively generated to match the sketched constraints using multiresolution surface deformation. In addition, the wavelet noise characteristics of silhouette strokes are propagated to the surrounding terrain. With terrain sketching users can interactively create or modify landscapes incorporating varied and complex landforms

Affective Scene Generation

A new technique for generating virtual environments is proposed, whereby the user describes the environment that they wish to create using adjectives. An entire scene is then procedurally generated, based on the mapping of these adjectives to the parameter space of the procedural models used. This mapping is determined through a pre-process, during which the user is presented with a number of scenes and asked to describe them using adjectives. With such a technique, the ability to create complex virtual environments is extended to users with little or no technical knowledge, and additionally provides a means for experienced users to quickly generate a large, complex environment which can then be modified by hand

A Comparison of Interactive Shadows and Multi-View Layouts for Mouse-based 3D Modelling

3D user interfaces allow users to view and interact with objects in a 3D scene and form a key component in many modelling applications used in engineering, medicine and design. Most mouse-based interfaces follow the same multi-view layout (three orthogonal, one perspective). This interface is difficult to understand, as it requires users to integrate all four views and build a 3D mental model. An alternative, Interactive Shadows, has been previously proposed that could improve on the multi-view's shortcomings but has never been formally tested. This paper presents the first quantitative user evaluation (n = 36) of both the multi-view and interactive shadows interfaces to compare their relative effectiveness and usability. Participants completed three types of tasks designed to be representative of object manipulation in current 3D modelling software. Interactive shadows were significantly better (p < 0,05) for tasks requiring participants to estimate distance. This suggests interactive shadows interface might better help users approximate relative object positioning

Compression of Dense and Regular Point Clouds

We present a simple technique for single-rate compression of point clouds sampled from a surface, based on a spanning tree of the points. Unlike previous methods, we predict future vertices using both a linear predictor, which uses the previous edge as a predictor for the current edge, and lateral predictors that rotate the previous edge 90 degrees left or right about an estimated normal. By careful construction of the spanning tree and choice of prediction rules, our method improves upon existing compression rates when applied to regularly sampled point sets, such as those produced by laser range scanning or uniform tesselation of higherorder surfaces. For less regular sets of points, the compression rate is still generally within 1.5 bits per point of other compression algorithms

Animation space: a truly linear framework for character animation

Skeletal subspace deformation (SSD), a simple method of character animation used in many applications, has several shortcomings; the best-known being that joints tend to collapse when bent. We present animation space, a generalization of SSD that greatly reduces these effects and effectively eliminates them for joints that do not have an unusually large range of motion.While other, more expensive generalizations exist, ours is unique in expressing the animation process as a simple linear transformation of the input coordinates. We show that linearity can be used to derive a measure of average distance (across the space of poses), and apply this to improving parametrizations.Linearity also makes it possible to fit a model to a set of examples using least-squares methods. The extra generality in animation space allows for a good fit to realistic data, and overfitting can be controlled to allow fitted models to generalize to new poses. Despite the extra vertex attributes, it is possible to render these animation-space models in hardware with no loss of performance relative to SSD