68 research outputs found
Distortion-free Displacement Mapping
Displacement mapping is routinely used to add geometric details in a fast and easy‐to‐control way, both in offline rendering as well as recently in interactive applications such as games. However, it went largely unnoticed (with the exception of McGuire and Whitson [MW08]) that, when applying displacement mapping to a surface with a low‐distortion parametrization, this parametrization is distorted as the geometry was changed by the displacement mapping. Typical resulting artifacts are “rubber band”‐like distortion patterns in areas of strong displacement change where a small isotropic area in texture space is mapped to a large anisotropic area in world space. We describe a fast, fully GPU‐based two‐step procedure to resolve this problem. First, a correction deformation is computed from the displacement map. Second, two variants to apply this correction when computing displacement mapping are proposed. The first variant is backward‐compatible and can resolve the artifact in any rendering pipeline without modifying it and without requiring additional computation at render time, but only works for bijective parametrizations. The second variant works for more general parametrizations, but requires to modify the rendering code and incurs a very small computational overhead
Simple quad domains for field aligned mesh parametrization
We present a method for the global parametrization of meshes that preserves alignment to a cross field in input while obtaining a parametric domain made of few coarse axis-aligned rectangular patches, which form an abstract base complex without T-junctions. The method is based on the topological simplification of the cross field in input, followed by global smoothing
Teoría de decisión bayesiana en los criterios de similitud utilizados en la segmentación de imágenes de rango
El obtener una imagen segmentada correctamente sigue siendo un asunto sin resolverse. Por lo general los resultados obtenidos por un computador al segmentar una imagen contienen sobre-segmentaciones, sub-segmentaciones y bordes mal definidos. En gran parte, estos inconvenientes recaen sobre el criterio de similitud utilizado por los algoritmos de segmentación. En el presente artículo se hace un análisis de los criterios de similitud más utilizados en la literatura y de la utilización de criterios basados en la teoría de decisión bayesiana
Coarse-grained Multiresolution Structures for Mobile Exploration of Gigantic Surface Models
We discuss our experience in creating scalable systems for distributing
and rendering gigantic 3D surfaces on web environments and
common handheld devices. Our methods are based on compressed
streamable coarse-grained multiresolution structures. By combining
CPU and GPU compression technology with our multiresolution
data representation, we are able to incrementally transfer, locally
store and render with unprecedented performance extremely
detailed 3D mesh models on WebGL-enabled browsers, as well as
on hardware-constrained mobile devices
Neural ShDF: Reviving an Efficient and Consistent Mesh Segmentation Method
Partitioning a polygonal mesh into meaningful parts can be challenging. Many
applications require decomposing such structures for further processing in
computer graphics. In the last decade, several methods were proposed to tackle
this problem, at the cost of intensive computational times. Recently, machine
learning has proven to be effective for the segmentation task on 3D structures.
Nevertheless, these state-of-the-art methods are often hardly generalizable and
require dividing the learned model into several specific classes of objects to
avoid overfitting. We present a data-driven approach leveraging deep learning
to encode a mapping function prior to mesh segmentation for multiple
applications. Our network reproduces a neighborhood map using our knowledge of
the \textsl{Shape Diameter Function} (SDF) method using similarities among
vertex neighborhoods. Our approach is resolution-agnostic as we downsample the
input meshes and query the full-resolution structure solely for neighborhood
contributions. Using our predicted SDF values, we can inject the resulting
structure into a graph-cut algorithm to generate an efficient and robust mesh
segmentation while considerably reducing the required computation times.Comment: 9 pages, 13 figures, and 3 tables. Short paper and poster published
and presented at SIGGRAPH 202
PolyCube-Maps
Standard texture mapping of real-world meshes suffers from the presence of seams that need to be introduced in order to avoid excessive distortions and to make the topology of the mesh compatible to the one of the texture domain. In contrast, cube maps provide a mechanism that could be used for seamless texture mapping with low distortion, but only if the object roughly resembles a cube. We extend this concept to arbitrary meshes by using as texture domain the surface of a polycube whose shape is similar to that of the given mesh. Our approach leads to a seamless texture mapping method that is simple enough to be implemented in currently available graphics hardware
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