8736539
A hole-filling strategy for reconstruction of smooth surfaces in range images
Creating models of real scenes is a complex task for which the use of traditional modelling techniques is inappropriate. For this task, laser rangefinders are frequently used to sample the scene from several viewpoints, with the resulting range images integrated into a final model. In practice, due to surface reflectance properties, occlusions and accessibility limitations, certain areas of the scenes are usually not sampled, leading to holes and introducing undesirable artifacts in the resulting models. We present an algorithm for filling holes on surfaces reconstructed from point clouds. The algorithm is based on moving least squares and can recover both geometry and shading information, providing a good alternative when the properties to be reconstructed are locally smooth. The reconstruction process is mostly automatic and the sampling rate in the reconstructed areas follows the given samples. We demonstrate the use of the algorithm on both real and synthetic data sets to obtain complete geometry and reasonable shading.
19002258
Reconstructing manifold and non-manifold surfaces from point clouds
This paper presents a novel approach for surface reconstruction from point clouds. The proposed technique is general in the sense that it naturally handles both manifold and non-manifold surfaces, providing a consistent way for reconstructing closed surfaces as well as surfaces with boundaries. It is also robust in the presence of noise, irregular sampling and surface gaps. Furthermore, it is fast, parallelizable and easy to implement because it is based on simple local operations. In this approach, surface reconstruction consists of three major steps: first, the space containing the point cloud is subdivided, creating a voxel representation. Then, a voxel surface is computed using gap filling and topological thinning operations. Finally, the resulting voxel surface is converted into a polygonal mesh. We demonstrate the effectiveness of our approach by reconstructing polygonal models from range scans of real objects as well as from synthetic data.
15090515
Filling holes on locally smooth surfaces reconstructed from point clouds
Abstract Creating models of real scenes is a complex task for which the use of traditional modeling techniques is inappropriate. For this task, laser rangefinders are frequently used to sample the scene from several viewpoints, with the resulting range images integrated into a final model. In practice, due to surface reflectance properties, occlusions and accessibility limitations, certain areas of the scenes are usually not sampled, leading to holes and introducing undesirable artifacts in the resulting models. We present an algorithm for filling holes on surfaces reconstructed from point clouds. The algorithm is based on moving least squares and can interpolate both geometry and shading information. The reconstruction process is mostly automatic and the sampling rate of the given samples is preserved in the reconstructed areas. We demonstrate the use of the algorithm on both real and synthetic datasets to obtain complete geometry and plausible shading.
2020901
Performance Modeling and Analysis of Web Switch
4384823
Capturing and rendering geometry details for BTF-mapped surfaces
Bidirectional texture functions, or BTFs, accurately model reflectance variation at a fine (meso-) scale as a function of lighting and viewing direction. BTFs also capture view-dependent visibility variation, also called masking or parallax, but only within surface contours. Mesostructure detail is neglected at silhouettes, so BTF-mapped objects retain the coarse shape of the underlying model.We augment BTF rendering to obtain approximate mesoscale silhouettes. Our new representation, the 4D mesostructure distance function (MDF), tabulates the displacement from a reference frame where a ray first intersects the mesoscale geometry beneath as a function of ray direction and ray position along that reference plane. Given an MDF, the mesostructure silhouette can be rendered with a per-pixel depth peeling process on graphics hardware, while shading and local parallax are handled by the BTF. Our approach allows real-time rendering, handles complex, non-height-field mesostructure, requires that no additional geometry be sent to the rasterizer other than the mesh triangles, is more compact than textured visibility representations used previously, and, for the first time, can be easily measured from physical samples. We also adapt the algorithm to capture detailed shadows cast both by and onto BTF-mapped surfaces. We demonstrate the efficiency of our algorithm on a variety of BTF data, including real data acquired using our BTF–MDF measurement system.
7700079
On 1-Arc-regular Graphs
A graph is 1-arc-regular if its full automorphism group acts regularly on the set of its arcs. In this paper, we investigate 1-arc-regular graphs of prime valency, especially of valency 3. First, we prove that if G is a soluble group then a (G, 1)-arc-regular graph must be a Cayley graph of a subgroup of G. Next we consider trivalent Cayley graphs of a finite nonabelian simple group and obtain a sufficient condition under which one can guarantee that Cay(G, S) is 1-arc-regular. Finally, as an application of the result, we construct two infinite families of 1-arc-regular trivalent Cayley graphs with insoluble automorphism groups and, in particular, one of the families is not a Cayley graph.
26189
Detecting Instances of Shape Classes That Exhibit Variable Structure
This paper proposes a method for detecting shapes of variable structure in images with clutter. The term “variable structure” means that some shape parts can be repeated an arbitrary number of times, some parts can be optional, and some parts can have several alternative appearances. The particular variation of the shape structure that occurs in a given image is not known a priori. Existing computer vision methods, including deformable model methods, were not designed to detect shapes of variable structure; they may only be used to detect shapes that can be decomposed into a fixed, a priori known, number of parts. The proposed method can handle both variations in shape structure and variations in the appearance of individual shape parts. A new class of shape models is introduced, called Hidden State Shape Models, that can naturally represent shapes of variable structure. A detection algorithm is described that finds instances of such shapes in images with large amounts of clutter by finding globally optimal correspondences between image features and shape models. Experiments with real images demonstrate that our method can localize plant branches that consist of an a priori unknown number of leaves and can detect hands more accurately than a hand detector based on the chamfer distance.
9468411
Is fair allocation always inefficient
This paper describes the tradeoff between fairness criteria of different allocation policies and throughput in a general network. A class of utility functions parameterized by a scalar defines a bandwidth allocation policy. An allocation is fair if the scalar is large and efficient if the aggregate source rate is large. The conjecture depends on the network topology in terms of routing and link capacities. A fairer allocation is always more efficient.