4,746 research outputs found
Static/Dynamic Filtering for Mesh Geometry
The joint bilateral filter, which enables feature-preserving signal smoothing
according to the structural information from a guidance, has been applied for
various tasks in geometry processing. Existing methods either rely on a static
guidance that may be inconsistent with the input and lead to unsatisfactory
results, or a dynamic guidance that is automatically updated but sensitive to
noises and outliers. Inspired by recent advances in image filtering, we propose
a new geometry filtering technique called static/dynamic filter, which utilizes
both static and dynamic guidances to achieve state-of-the-art results. The
proposed filter is based on a nonlinear optimization that enforces smoothness
of the signal while preserving variations that correspond to features of
certain scales. We develop an efficient iterative solver for the problem, which
unifies existing filters that are based on static or dynamic guidances. The
filter can be applied to mesh face normals followed by vertex position update,
to achieve scale-aware and feature-preserving filtering of mesh geometry. It
also works well for other types of signals defined on mesh surfaces, such as
texture colors. Extensive experimental results demonstrate the effectiveness of
the proposed filter for various geometry processing applications such as mesh
denoising, geometry feature enhancement, and texture color filtering
3D mesh metamorphosis from spherical parameterization for conceptual design
Engineering product design is an information intensive decision-making
process that consists of several phases including design specification
definition, design concepts generation, detailed design and analysis,
and manufacturing. Usually, generating geometry models for
visualization is a big challenge for early stage conceptual design.
Complexity of existing computer aided design packages constrains
participation of people with various backgrounds in the design
process. In addition, many design processes do not take advantage of
the rich amount of legacy information available for new concepts
creation.
The research presented here explores the use of advanced graphical
techniques to quickly and efficiently merge legacy information with
new design concepts to rapidly create new conceptual product designs.
3D mesh metamorphosis framework 3DMeshMorpher was created to
construct new models by navigating in a shape-space of registered
design models. The framework is composed of: i) a fast spherical
parameterization method to map a geometric model (genus-0) onto a unit
sphere; ii) a geometric feature identification and picking technique
based on 3D skeleton extraction; and iii) a LOD controllable 3D
remeshing scheme with spherical mesh subdivision based on the
developedspherical parameterization. This efficient software framework
enables designers to create numerous geometric concepts in real time
with a simple graphical user interface.
The spherical parameterization method is focused on closed genus-zero
meshes. It is based upon barycentric coordinates with convex boundary.
Unlike most existing similar approaches which deal with each vertex in
the mesh equally, the method developed in this research focuses
primarily on resolving overlapping areas, which helps speed the
parameterization process. The algorithm starts by normalizing the
source mesh onto a unit sphere and followed by some initial relaxation
via Gauss-Seidel iterations. Due to its emphasis on solving only
challenging overlapping regions, this parameterization process is much
faster than existing spherical mapping methods.
To ensure the correspondence of features from different models, we
introduce a skeleton based feature identification and picking method
for features alignment. Unlike traditional methods that align single
point for each feature, this method can provide alignments for
complete feature areas. This could help users to create more
reasonable intermediate morphing results with preserved topological
features. This skeleton featuring framework could potentially be
extended to automatic features alignment for geometries with similar
topologies. The skeleton extracted could also be applied for other
applications such as skeleton-based animations.
The 3D remeshing algorithm with spherical mesh subdivision is
developed to generate a common connectivity for different mesh models.
This method is derived from the concept of spherical mesh subdivision.
The local recursive subdivision can be set to match the desired LOD
(level of details) for source spherical mesh. Such LOD is controllable
and this allows various outputs with different resolutions. Such
recursive subdivision then follows by a triangular correction process
which ensures valid triangulations for the remeshing. And the final
mesh merging and reconstruction process produces the remeshing model
with desired LOD specified from user. Usually the final merged model
contains all the geometric details from each model with reasonable
amount of vertices, unlike other existing methods that result in big
amount of vertices in the merged model. Such multi-resolution outputs
with controllable LOD could also be applied in various other computer
graphics applications such as computer games
A Revisit of Shape Editing Techniques: from the Geometric to the Neural Viewpoint
3D shape editing is widely used in a range of applications such as movie
production, computer games and computer aided design. It is also a popular
research topic in computer graphics and computer vision. In past decades,
researchers have developed a series of editing methods to make the editing
process faster, more robust, and more reliable. Traditionally, the deformed
shape is determined by the optimal transformation and weights for an energy
term. With increasing availability of 3D shapes on the Internet, data-driven
methods were proposed to improve the editing results. More recently as the deep
neural networks became popular, many deep learning based editing methods have
been developed in this field, which is naturally data-driven. We mainly survey
recent research works from the geometric viewpoint to those emerging neural
deformation techniques and categorize them into organic shape editing methods
and man-made model editing methods. Both traditional methods and recent neural
network based methods are reviewed
Mesh-based Gaussian Splatting for Real-time Large-scale Deformation
Neural implicit representations, including Neural Distance Fields and Neural
Radiance Fields, have demonstrated significant capabilities for reconstructing
surfaces with complicated geometry and topology, and generating novel views of
a scene. Nevertheless, it is challenging for users to directly deform or
manipulate these implicit representations with large deformations in the
real-time fashion. Gaussian Splatting(GS) has recently become a promising
method with explicit geometry for representing static scenes and facilitating
high-quality and real-time synthesis of novel views. However,it cannot be
easily deformed due to the use of discrete Gaussians and lack of explicit
topology. To address this, we develop a novel GS-based method that enables
interactive deformation. Our key idea is to design an innovative mesh-based GS
representation, which is integrated into Gaussian learning and manipulation. 3D
Gaussians are defined over an explicit mesh, and they are bound with each
other: the rendering of 3D Gaussians guides the mesh face split for adaptive
refinement, and the mesh face split directs the splitting of 3D Gaussians.
Moreover, the explicit mesh constraints help regularize the Gaussian
distribution, suppressing poor-quality Gaussians(e.g. misaligned
Gaussians,long-narrow shaped Gaussians), thus enhancing visual quality and
avoiding artifacts during deformation. Based on this representation, we further
introduce a large-scale Gaussian deformation technique to enable deformable GS,
which alters the parameters of 3D Gaussians according to the manipulation of
the associated mesh. Our method benefits from existing mesh deformation
datasets for more realistic data-driven Gaussian deformation. Extensive
experiments show that our approach achieves high-quality reconstruction and
effective deformation, while maintaining the promising rendering results at a
high frame rate(65 FPS on average).Comment: 11 pages, 7 figure
Sketching-based Skeleton Extraction
Articulated character animation can be performed by manually creating and rigging a skeleton into an unfolded 3D mesh model. Such tasks are not trivial, as they require a substantial amount of training and practice. Although methods have been proposed to help automatic extraction of skeleton structure, they may not guarantee that the resulting skeleton can help to produce animations according to user manipulation. We present a sketching-based skeleton extraction method to create a user desired skeleton structure which is used in 3D model animation. This method takes user sketching as an input, and based on the mesh segmentation result of a 3D mesh model, generates a skeleton for articulated character animation.
In our system, we assume that a user will properly sketch bones by roughly following the mesh model structure. The user is expected to sketch independently on different regions of a mesh model for creating separate bones. For each sketched stroke, we project it into the mesh model so that it becomes the medial axis of its corresponding mesh model region from the current viewer perspective. We call this projected stroke a “sketched bone”. After pre-processing user sketched bones, we cluster them into groups. This process is critical as user sketching can be done from any orientation of a mesh model. To specify the topology feature for different mesh parts, a user can sketch strokes from different orientations of a mesh model, as there may be duplicate strokes from different orientations for the same mesh part. We need a clustering process to merge similar sketched bones into one bone, which we call a “reference bone”. The clustering process is based on three criteria: orientation, overlapping and locality.
Given the reference bones as the input, we adopt a mesh segmentation process to assist our skeleton extraction method. To be specific, we apply the reference bones and the seed triangles to segment the input mesh model into meaningful segments using a multiple-region growing mechanism. The seed triangles, which are collected from the reference bones, are used as the initial seeds in the mesh segmentation process. We have designed a new segmentation metric [1] to form a better segmentation criterion. Then we compute the Level Set Diagrams (LSDs) on each mesh part to extract bones and joints. To construct the final skeleton, we connect bones extracted from all mesh parts together into a single structure.
There are three major steps involved: optimizing and smoothing bones, generating joints and forming the skeleton structure. After constructing the skeleton model, we have proposed a new method, which utilizes the Linear Blend Skinning (LBS) technique and the Laplacian mesh deformation technique together to perform skeleton-driven animation. Traditional LBS techniques may have self-intersection problem in regions around segmentation boundaries. Laplacian mesh deformation can preserve the local surface details, which can eliminate the self-intersection problem. In this case, we make use of LBS result as the positional constraint to perform a Laplacian mesh deformation. By using the Laplacian mesh deformation method, we maintain the surface details in segmentation boundary regions.
This thesis outlines a novel approach to construct a 3D skeleton model interactively, which can also be used in 3D animation and 3D model matching area. The work is motivated by the observation that either most of the existing automatic skeleton extraction methods lack well-positioned joints specification or the manually generated methods require too much professional training to create a good skeleton structure. We dedicate a novel approach to create 3D model skeleton based on user sketching which specifies articulated skeleton with joints. The experimental results show that our method can produce better skeletons in terms of joint positions and topological structure
TetSplat: Real-time Rendering and Volume Clipping of Large Unstructured Tetrahedral Meshes
We present a novel approach to interactive visualization and exploration of large unstructured tetrahedral meshes. These massive 3D meshes are used in mission-critical CFD and structural mechanics simulations, and typically sample multiple field values on several millions of unstructured grid points. Our method relies on the pre-processing of the tetrahedral mesh to partition it into non-convex boundaries and internal fragments that are subsequently encoded into compressed multi-resolution data representations. These compact hierarchical data structures are then adaptively rendered and probed in real-time on a commodity PC. Our point-based rendering algorithm, which is inspired by QSplat, employs a simple but highly efficient splatting technique that guarantees interactive frame-rates regardless of the size of the input mesh and the available rendering hardware. It furthermore allows for real-time probing of the volumetric data-set through constructive solid geometry operations as well as interactive editing of color transfer functions for an arbitrary number of field values. Thus, the presented visualization technique allows end-users for the first time to interactively render and explore very large unstructured tetrahedral meshes on relatively inexpensive hardware
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