931 research outputs found
Frequency Analysis of Gradient Estimators in Volume Rendering
Gradient information is used in volume rendering to classify and color samples along a ray. In this paper, we present an analysis of the theoretically ideal gradient estimator and compare it to some commonly used gradient estimators. A new method is presented to calculate the gradient at arbitrary sample positions, using the derivative of the interpolation filter as the basis for the new gradient filter. As an example, we will discuss the use of the derivative of the cubic spline. Comparisons with several other methods are demonstrated. Computational efficiency can be realized since parts of the interpolation computation can be leveraged in the gradient estimatio
Digital objects in rhombic dodecahedron grid
Rhombic dodecahedron is a space filling polyhedron which represents the close packing of spheres in 3D space and the Voronoi structures of the face centered cubic (FCC) lattice. In this paper, we describe a new coordinate system where every 3-integer coordinates grid point corresponds to a rhombic dodecahedron centroid. In order to illustrate the interest of the new coordinate system, we propose the characterization of 3D digital plane with its topological features, such as the interrelation between the thickness of the digital plane and the separability constraint we aim to obtain. We also present the characterization of 3D digital lines and study it as the intersection of multiple digital planes. Characterization of 3D digital sphere with relevant topological features is proposed as well along with the 48-symmetry appearing in the new coordinate system
Distance-based skeletonization on the BCC grid
Strand proposed a distance-based thinning algorithm for computing surface skeletons on the body-centered cubic (BCC) grid. In this paper, we present two modified versions of this algorithm that are faster than the original one, and less sensitive to the visiting order of points in the sequential thinning phase. In addition, a novel algorithm capable of producing curve skeletons is also reported
Time-varying volume visualization
Volume rendering is a very active research field in Computer Graphics because of its wide range of applications in various sciences, from medicine to flow mechanics. In this report, we survey a state-of-the-art on time-varying volume rendering. We state several basic concepts and then we establish several criteria to classify the studied works: IVR versus DVR, 4D versus 3D+time, compression techniques, involved architectures, use of parallelism and image-space versus object-space coherence. We also address other related problems as transfer functions and 2D cross-sections computation of time-varying volume data. All the papers reviewed are classified into several tables based on the mentioned classification and, finally, several conclusions are presented.Preprin
Computerized Classification of Surface Spikes in Three-Dimensional Electron Microscopic Reconstructions of Viruses
The purpose of this research is to develop computer techniques for improved three-dimensional (3D) reconstruction of viruses from electron microscopic images of them and for the subsequent improved classification of the surface spikes in the resulting reconstruction. The broader impact of such work is the following.
Influenza is an infectious disease caused by rapidly-changing viruses that appear seasonally in the human population. New strains of influenza viruses appear every year, with the potential to cause a serious global pandemic. Two kinds of spikes – hemagglutinin (HA) and neuraminidase (NA) – decorate the surface of the virus particles and these proteins are primarily responsible for the antigenic changes observed in influenza viruses. Identification of the locations of the surface spikes of both kinds in a new strain of influenza virus can be of critical importance for the development of a vaccine that protects against such a virus.
Two major categories of reconstruction techniques are transform methods such as weighted backprojection (WBP) and series expansion methods such as the algebraic reconstruction techniques (ART) and the simultaneous iterative reconstruction technique (SIRT). Series expansion methods aim at estimating the object to be reconstructed by a linear combination of some fixed basis functions and they typically estimate the coefficients in such an expansion by an iterative algorithm. The choice of the set of basis functions greatly influences the efficacy of the output of a series expansion method. It has been demonstrated that using spherically symmetric basis functions (blobs), instead of the more traditional voxels, results in reconstructions of superior quality. Our own research shows that, with the recommended data-processing steps performed on the projection images prior to reconstruction, ART (with its free parameters appropriately tuned) provides 3D reconstructions of viruses from tomographic tilt series that allow reliable quantification of the surface proteins and that the same is not achieved using WBP or SIRT, which are the methods that have been routinely applied by practicing electron microscopists.
Image segmentation is the process of recognizing different objects in an image. Segmenting an object from a background is not a trivial task, especially when the image is corrupted by noise and/or shading. One concept that has been successfully used to achieve segmentation in such corrupted images is fuzzy connectedness. This technique assigns to each element in an image a grade of membership in an object.
Classifications methods use set of relevant features to identify the objects of each class. To distinguish between HA and NA spikes in this research, discussions with biologists suggest that there may be a single feature that can be used reliably for the classification process. The result of the fuzzy connectedness technique we conducted to segment spikes from the background confirms the correctness of the biologists’ assumption. The single feature we used is the ratio of the width of the spike’s head to the width of its stem in 3D space; the ratio appears to be greater for NA than it is for HA. The proposed classifier is tested on different types of 3D reconstructions derived from simulated data. A statistical hypothesis testing based methodology allowed us to evaluate the relative suitability of reconstruction methods for the given classification task
Discrete Imaging Models for Three-Dimensional Optoacoustic Tomography using Radially Symmetric Expansion Functions
Optoacoustic tomography (OAT), also known as photoacoustic tomography, is an
emerging computed biomedical imaging modality that exploits optical contrast
and ultrasonic detection principles. Iterative image reconstruction algorithms
that are based on discrete imaging models are actively being developed for OAT
due to their ability to improve image quality by incorporating accurate models
of the imaging physics, instrument response, and measurement noise. In this
work, we investigate the use of discrete imaging models based on Kaiser-Bessel
window functions for iterative image reconstruction in OAT. A closed-form
expression for the pressure produced by a Kaiser-Bessel function is calculated,
which facilitates accurate computation of the system matrix.
Computer-simulation and experimental studies are employed to demonstrate the
potential advantages of Kaiser-Bessel function-based iterative image
reconstruction in OAT
Topomap: Topological Mapping and Navigation Based on Visual SLAM Maps
Visual robot navigation within large-scale, semi-structured environments
deals with various challenges such as computation intensive path planning
algorithms or insufficient knowledge about traversable spaces. Moreover, many
state-of-the-art navigation approaches only operate locally instead of gaining
a more conceptual understanding of the planning objective. This limits the
complexity of tasks a robot can accomplish and makes it harder to deal with
uncertainties that are present in the context of real-time robotics
applications. In this work, we present Topomap, a framework which simplifies
the navigation task by providing a map to the robot which is tailored for path
planning use. This novel approach transforms a sparse feature-based map from a
visual Simultaneous Localization And Mapping (SLAM) system into a
three-dimensional topological map. This is done in two steps. First, we extract
occupancy information directly from the noisy sparse point cloud. Then, we
create a set of convex free-space clusters, which are the vertices of the
topological map. We show that this representation improves the efficiency of
global planning, and we provide a complete derivation of our algorithm.
Planning experiments on real world datasets demonstrate that we achieve similar
performance as RRT* with significantly lower computation times and storage
requirements. Finally, we test our algorithm on a mobile robotic platform to
prove its advantages.Comment: 8 page
MeshDiffusion: Score-based Generative 3D Mesh Modeling
We consider the task of generating realistic 3D shapes, which is useful for a
variety of applications such as automatic scene generation and physical
simulation. Compared to other 3D representations like voxels and point clouds,
meshes are more desirable in practice, because (1) they enable easy and
arbitrary manipulation of shapes for relighting and simulation, and (2) they
can fully leverage the power of modern graphics pipelines which are mostly
optimized for meshes. Previous scalable methods for generating meshes typically
rely on sub-optimal post-processing, and they tend to produce overly-smooth or
noisy surfaces without fine-grained geometric details. To overcome these
shortcomings, we take advantage of the graph structure of meshes and use a
simple yet very effective generative modeling method to generate 3D meshes.
Specifically, we represent meshes with deformable tetrahedral grids, and then
train a diffusion model on this direct parametrization. We demonstrate the
effectiveness of our model on multiple generative tasks.Comment: Published in ICLR 2023 (Spotlight, Notable-top-25%
- …