Geometric Reconstructions Research Articles

Real-time volume rendering with octree-based implicit surface representation

Recent breakthroughs in neural radiance fields have significantly advanced the field of novel view synthesis and 3D reconstruction from multi-view images. However, the prevalent neural volume rendering techniques often suffer from long rendering time and require extensive network training. To address these limitations, recent initiatives have explored explicit voxel representations of scenes to expedite training. Yet, they often fall short in delivering accurate geometric reconstructions due to a lack of effective 3D representation. In this paper, we propose an octree-based approach for the reconstruction of implicit surfaces from multi-view images. Leveraging an explicit, network-free data structure, our method substantially increases rendering speed, achieving real-time performance. Moreover, our reconstruction technique yields surfaces with quality comparable to state-of-the-art network-based learning methods. The source code and data can be downloaded from https://github.com/LaoChui999/Octree-VolSDF.

3D DENSITY-GRADIENT BASED EDGE DETECTION ON NEURAL RADIANCE FIELDS (NERFS) FOR GEOMETRIC RECONSTRUCTION

Abstract. Generating geometric 3D reconstructions from Neural Radiance Fields (NeRFs) is of great interest. However, accurate and complete reconstructions based on the density values are challenging. The network output depends on input data, NeRF network configuration and hyperparameter. As a result, the direct usage of density values, e.g. via filtering with global density thresholds, usually requires empirical investigations. Under the assumption that the density increases from non-object to object area, the utilization of density gradients from relative values is evident. As the density represents a position-dependent parameter it can be handled anisotropically, therefore processing of the voxelized 3D density field is justified. In this regard, we address geometric 3D reconstructions based on density gradients, whereas the gradients result from 3D edge detection filters of the first and second derivatives, namely Sobel, Canny and Laplacian of Gaussian. The gradients rely on relative neighboring density values in all directions, thus are independent from absolute magnitudes. Consequently, gradient filters are able to extract edges along a wide density range, almost independent from assumptions and empirical investigations. Our approach demonstrates the capability to achieve geometric 3D reconstructions with high geometric accuracy on object surfaces and remarkable object completeness. Notably, Canny filter effectively eliminates gaps, delivers a uniform point density, and strikes a favorable balance between correctness and completeness across the scenes.

The influence of fossils in macroevolutionary analyses of 3D geometric morphometric data: A case study of galloanseran quadrates.

In birds and other reptiles, the quadrate acts as a hinge between the lower jaw and the skull and plays an important role in avian cranial kinesis. Though previous studies have qualitatively described substantial variation in quadrate morphology among birds, none have attempted to quantify evolutionary changes in quadrate shape. Here, we investigate geometric evolution of the quadrate in Galloanserae, a major clade of extant birds uniting chicken-like (Galliformes) and duck-like (Anseriformes) fowl. We quantified morphological variation in the quadrate across 50 extant galloanseran species covering all major extant subclades using three-dimensional geometric morphometrics, and performed ancestral shape reconstructions in the context of an up-to-date neornithine phylogeny. We find that our results based only on extant quadrates may overlook plesiomorphic features captured by fossil taxa, resulting in an ancestral state reconstruction for Galloanserae that is seemingly an approximation of the average shape of the extant data set. By contrast, analyses incorporating early fossil galloanseran quadrates (from taxa such as Asteriornis, Presbyornis, and Conflicto) result in ancestral geometric reconstructions more similar to the morphology of extant galliforms, indicating that the quadrate of the last common ancestor of galloanserans may have been more morphologically and functionally similar to those of extant galliforms than to extant anseriforms. These results generally corroborate previous inferences of galloanseran quadrate plesiomorphies and identify several additional plesiomorphic features of the galloanseran quadrate for the first time. Our results illustrate the importance of incorporating fossil taxa into ancestral shape reconstructions and help elucidate important aspects of the morphology and function of the avian feeding apparatus early in crown bird evolutionary history.

Inverse design of 3D reconfigurable curvilinear modular origami structures using geometric and topological reconstructions

The recent development of modular origami structures has ushered in an era for active metamaterials with multiple degrees of freedom (multi-DOF). Notably, no systematic inverse design approach for 3D curvilinear modular origami structures has been reported. Moreover, very few modular origami topologies have been studied to design active metamaterials with multi-DOF. Herein, we develop an inverse design method for constructing 3D reconfigurable architected structures — we synthesize modular origami structures whose unit cells can be volumetrically mapped into a prescribed 3D curvilinear shape followed by volumetric shrinkage to construct modules. After modification of the tubular geometry, we search through all the possible geometric and topological combinations of the modular origami structures to attain the target mobility using a topological reconstruction of modules. Our inverse design using geometric and topological reconstructions can provide an effective solution to construct 3D curvilinear reconfigurable structures with multi-DOF. Our work opens a path toward 3D reconfigurable systems based on volumetric inverse design, such as 3D active metamaterials and 3D morphing devices for automotive, aerospace, and biomedical engineering applications.

Locally-guided neural denoising

Noise-like artifacts are common in measured or fitted data across various domains, e.g. photography, geometric reconstructions in terms of point clouds or meshes, as well as reflectance measurements and the respective fitting of commonly used reflectance models to them. State-of-the-art denoising approaches focus on specific noise characteristics usually observed in photography. However, these approaches do not perform well if data is corrupted with location-dependent noise. A typical example is the acquisition of heterogeneous materials, which leads to different noise levels due to different behavior of the components either during acquisition or during reconstruction. We address this problem by first automatically determining location-dependent noise levels in the input data and demonstrate that state-of-the-art denoising algorithms can usually benefit from this guidance with only minor modifications to their loss function or employed regularization mechanisms. To generate this information for guidance, we analyze patchwise variances and subsequently derive per-pixel importance values. We demonstrate the benefits of such locally-guided denoising at the examples of the Deep Image Prior method and the Self2Self method.

Optical coherence tomography refraction and optical path length correction for image-guided corneal surgery.

Optical coherence tomography (OCT) may be useful for guidance of ocular microsurgeries such as deep anterior lamellar keratoplasty (DALK), a form of corneal transplantation that requires delicate insertion of a needle into the stroma to approximately 90% of the corneal thickness. However, visualization of the true shape of the cornea and the surgical tool during surgery is impaired in raw OCT volumes due to both light refraction at the corneal boundaries, as well as geometrical optical path length distortion due to the group velocity of broadband OCT light in tissue. Therefore, uncorrected B-scans or volumes may not provide an accurate visualization suitable for reliable surgical guidance. In this article, we introduce a method to correct for both refraction and optical path length distortion in 3D in order to reconstruct corrected OCT B-scans in both natural corneas and corneas deformed by needle insertion. We delineate the separate roles of phase and group index in OCT image distortion correction, and introduce a method to estimate the phase index from the group index which is readily measured in samples. Using the measured group index and estimated phase index of human corneas at 1060 nm, we demonstrate quantitatively accurate geometric reconstructions of the true cornea and inserted needle shape during simulated DALK surgeries.

Otosclerosis under microCT: New insights into the disease and its anatomy.

Otospongiotic plaques can be seen on conventional computed tomography (CT) as focal lesions around the cochlea. However, the resolution remains insufficient to enable evaluation of intracochlear damage. MicroCT technology provides resolution at the single micron level, offering an exceptional amplified view of the otosclerotic cochlea. In this study, a non-decalcified otosclerotic cochlea was analyzed and reconstructed in three dimensions for the first time, using microCT technology. The pre-clinical relevance of this study is the demonstration of extensive pro-inflammatory buildup inside the cochlea which cannot be seen with conventional cone-beam CT (CBCT) investigation. A radiological and a three-dimensional (3D) anatomical study of an otosclerotic cochlea using microCT technology is presented here for the first time. 3D-segmentation of the human cochlea was performed, providing an unprecedented view of the diseased area without the need for decalcification, sectioning, or staining. Using microCT at single micron resolution and geometric reconstructions, it was possible to visualize the disease's effects. These included intensive tissue remodeling and highly vascularized areas with dilated capillaries around the spongiotic foci seen on the pericochlear bone. The cochlea's architecture as a morphological correlate of the otosclerosis was also seen. With a sagittal cut of the 3D mesh, it was possible to visualize intense ossification of the cochlear apex, as well as the internal auditory canal, the modiolus, the spiral ligament, and a large cochleolith over the osseous spiral lamina. In addition, the oval and round windows showed intense fibrotic tissue formation and spongiotic bone with increased vascularization. Given the recently described importance of the osseous spiral lamina in hearing mechanics and that, clinically, one of the signs of otosclerosis is the Carhart notch observed on the audiogram, a tonotopic map using the osseous spiral lamina as region of interest is presented. An additional quantitative study of the porosity and width of the osseous spiral lamina is reported. In this study, structural anatomical alterations of the otosclerotic cochlea were visualized in 3D for the first time. MicroCT suggested that even though the disease may not appear to be advanced in standard clinical CT scans, intense tissue remodeling is already ongoing inside the cochlea. That knowledge will have a great impact on further treatment of patients presenting with sensorineural hearing loss.

The influence of glacial topography on fluvial efficiency in the Teton Range, Wyoming (USA)

This study examines the role of topography as a dynamic boundary condition that limits the efficiency of fluvial erosion in the post-glacial Teton Range landscape. The volume of sediment currently stored in two major catchments was estimated using high-resolution LiDAR and geometric reconstructions of depth to bedrock. Seismic reflection data in Moran Bay reveals post-glacial sediment preserved behind a submerged moraine, which isolates the bay from the larger Jackson Lake depocenter. The volume of post-glacial sediment stored in the canyons and bay totals 173.82 ± 19.5336.0 (×10−3 km3), which translates to a catchment-wide sediment production rate of 0.17 ± 0.02 mm/yr. The rock-equivalent sediment volume in Moran Bay is 4.4 ± 0.9 (×10−3 km3), only ∼2.6% of the total post-glacial volume. While the estimated sediment production rate in the canyons is similar to the uplift rate, the denudation rate derived from Moran Bay sediment is 0.004 ± 0.001 mm/yr, implying highly inefficient post-glacial sediment transport. The fluvial system has been disequilibrated by glacial erosion such that interglacial valley profiles lack the steepness needed to transport sediment, delaying sediment evacuation until the next glacial advance, or until uplift sufficiently steepens the fluvial system so that it regains efficiency. Furthermore, colluvial production rates in the deglaciated valleys are close to long-term denudation and uplift rates, suggesting that once topography has been equilibrated to glacial erosion processes, subsequent glaciers do not need to produce much bedrock erosion, but mainly sweep out accumulated sediment to maintain equilibrium.

Three Dimensional Reconstruction of Botanical Trees with Simulatable Geometry

We tackle the challenging problem of creating full and accurate three dimensional reconstructions of botanical trees with the topological and geometric accuracy required for subsequent physical simulation, e.g. in response to wind forces. Although certain aspects of our approach would benefit from various improvements, our results exceed the state of the art especially in geometric and topological complexity and accuracy. Starting with two dimensional RGB image data acquired from cameras attached to drones, we create point clouds, textured triangle meshes, and a simulatable and skinned cylindrical articulated rigid body model. We discuss the pros and cons of each step of our pipeline, and in order to stimulate future research we make the raw and processed data from every step of the pipeline as well as the final geometric reconstructions publicly available.

Two-Dimensional Planar BGe Monolayer as an Anode Material for Sodium-Ion Batteries.

Using first-principles swarm intelligence structure prediction computations, we explore a fully planar BGe monolayer with unique mechanical and electrical properties. Theoretical calculations reveal that a free-standing BGe monolayer has excellent stability, which is confirmed by the cohesive energy (compared to experimentally synthetic borophene and germanene monolayers), phonon modes (no imaginary frequencies appeared in the phonon spectrum), ab initio molecular dynamics (AIMD) simulations (no broken bonds and geometric reconstructions), and mechanical stability criteria. The metallic feature of the BGe monolayer can be maintained after absorbing different numbers of Na atoms, ensuring good electronic conductivity during the charge/discharge process. The calculated migration energy barrier, open-circuit voltage, and theoretical specific capacity of the BGe monolayer are much better than those of some other two-dimensional (2D) materials. These findings render the BGe monolayer a potential candidate for reversible Na-ion battery anode materials with desirable performance.

Multi-material hydrodynamics with algebraic sharp interface capturing

A finite volume method for Eulerian multi-material hydrodynamics with sharp interface capturing is presented. The pressure-temperature non-equilibrium multi-material system with finite-rate pressure relaxation in mixed-cells is considered here. This pressure closure facilitates material-property-dependent pressure relaxation, rather than instantaneous pressure equilibration, which in turn allows the use of unsplit high-order time-integrators. A modified tangent of hyperbola for interface capturing (THINC) method is used to reconstruct multi-material (>2) interfaces, on three-dimensional unstructured meshes. A simple modification which extends the THINC reconstruction to interfaces between more than two materials is proposed. It is demonstrated that the modified THINC can capture multi-material interfaces within 2–4 tetrahedral cells. Since no geometric reconstructions are required by the THINC method, the presented multi-material method is algorithmically simple, and computationally efficient. Consistent reconstructions of conserved quantities at material interfaces ensure that conservation and closure laws are satisfied at the discrete level. Through a suite of test problems solved on unstructured meshes, it is demonstrated that the presented method is a promising candidate for accurate and efficient multi-material hydrodynamics computations.

A Distributed Approach for the Implementation of Geometric Reconstruction-Based Visual SLAM Systems

SUMMARYVisual simultaneous localization and mapping (VSLAM) is a relevant solution for vehicle localization and mapping environments. However, it is computationally expensive because it demands large computational effort, making it a non-real-time solution. The VSLAM systems that employ geometric reconstructions are based on the parallel processing paradigm developed in the Parallel Tracking and Mapping (PTAM) algorithm. This type of system was created for processors that have exactly two cores. The various SLAM methods based on the PTAM were also not designed to scale to all the cores of modern processors nor to function as a distributed system. Therefore, we propose a modification to the pipeline for the execution of well-known VSLAM systems so that they can be scaled to all available processors during execution, thereby increasing their performance in terms of processing time. We explain the principles behind this modification via a study of the threads in the SLAM systems based on PTAM. We validate our results with experiments describing the behavior of the original ORB-SLAM system and the modified version.

Numerical study on effective thermal conductivities of plain woven C/SiC composites with considering pores in interlaced woven yarns

Plain woven C/SiC composites have been widely applied in engineering thermal protective structures due to their excellent mechanical and physical properties. Plain woven C/SiC orthotropic composites are composed of carbon fibers, and in-yarn and out-of-yarn SiC matrixes with small air pores. Experimental studies on the effective thermal conductivities of plain woven C/SiC composites are rare due to their complex structure and costly processing technology. The effects of fiber volume fraction and porosity on the effective thermal conductivities can be revealed by numerical approach. In the present study, a finite volume numerical model at three scale levels is proposed on the basis of 3D geometric reconstructions with in-yarn and out-of-yarn porosities. The thermal conductivities of SiC matrix, woven yarn, and plain woven C/SiC composites are predicted using up-scaling approach. The proposed model is validated using available analytical and experimental results. The thermal conductivities of plain woven C/SiC composites decrease with the increment in carbon fiber volume fraction, and in-yarn and out-of-yarn porosities. The effect of out-of-yarn porosity on the thermal conductivities of the composites plays a dominant role. However, the occurrence of in-yarn porosity can lead to maximum decreases of 3.1% and 5.6% for in-plane and out-of-plane thermal conductivities respectively compared with the case without in-yarn porosity. The present work can provide a scientific guidance for the thermal design of plain woven C/SiC composites.

Pore-Network Reconstruction and Simulation of the Fuel Cell Catalyst Layer

Fuel cell technology is widely considered as a promising green alternative to the current internal combustion engines. Nevertheless, they are still expensive and therefore not economically viable for the majority. Among others, platinum underutilization in the catalyst layer is known problem that if tackled leads to a significant price reduction. The difficulty of this task stems from the very small size of the catalyst layer which makes it extremely difficult to probe experimentally. Consequently, modeling has been proven useful to give insights about the influencing factors in the catalyst layer and how they affect the overall performance of the fuel cell. Recently, pore-scale modeling has been employed to better understand transport phenomena at microscopic level. Nevertheless, because of the exponential computing requirements, most studies had to limit their scope either in domain size or resolution, which has two direct consequences: (a) the results may not be representative, and (b) they are not truly predictive. We propose a pore-scale model for the catalyst layer in the nanometer scale. Resolving the catalyst layer at this scale is unprecedented to the best of our knowledge. The model is based on pore-networks, i.e. mapping the porous structure onto an intricate network of pores connected through arbitrary throats. The underlying assumption in pore network models is that intensive properties are constant throughout each pore. Given the extremely small scale of pores in the catalyst layer, i.e. ~100 um, this assumption is reasonable. While pore network models inevitably introduce a small error, they reduce the computing requirement by 4 orders of magnitude or more. This feature allows for studying much larger domains with the same computing power. First, we digitally reconstruct the microstructure of the catalyst layer based on a process-based technique introduced by [1]. The reconstructed geometry is in the form of a 3d image and consists of 4 distinct phases: carbon support, platinum, nafion, and void. Using a network extraction algorithm [2], the equivalent networks corresponding to the void and carbon phases are extracted. We propose a simple algorithm to couple the two extracted networks with the remainder of the original 3d image, which now only consists of nafion and platinum. Finally, the diffusive transport of oxygen coupled with conductive transport of protons and electrons with the electrochemistry at the interface of nafion and platinum is solved through an iterative scheme. The results are reported in terms of effective properties and polarization curves. The effect of microstructural features such as nafion content and platinum loading on such properties are studied. All the geometric reconstructions and transport simulations were done with the open-source code OpenPNM [3]. The present study is a major step towards better understanding the multiphysics involved in the catalyst layer at true pore scale. The pore network methodology used in this study was key to significantly reducing the computing requirements that otherwise have hindered studying the catalyst layer at higher resolutions. We hope that this study will become a cornerstone for many future studies.

SkeletonFusion: Reconstruction and tracking of human body in real-time

This paper presents a new pipeline for capturing the performance of the human body with two depth cameras in real time. Our online approach reconstructs not only the movement of the skeleton, but also the dense nonrigid 3D surface. The key to our algorithm is a coarse-to-fine strategy: large-scale deformations or rapid movements are captured by the skeleton pose tracker, with which the dense volumetric 6D motion field can be estimated robustly for dense geometry reconstruction. Shown in various sequences, our approach was able to accurately capture the 3D motion of the human body and produce increasingly denoised, detailed, and complete geometric reconstructions.

Coupling of Pore-Phase and Solid-Phase Networks for Simulating Heat and Mass Transport in Porous Transport Layers

Reactant, water, and heat transport through Porous Transport Layers (PTL), also known as Gas Diffusion Layers (GDL), can be simulated using a variety of computational architectures and transport models. A common approach is to create detailed reconstruction of geometry from tomographic data and use a Lattice-Boltzmann model for computing transport within the material. Another common approach is to simulate the material using a network of transport resistance elements and then use continuum, phenomenological, or Lattice Boltzmann models for computing transport through the network. For either approach the computational domain should be representative of the morphology and structure of the PTL being simulated. Geometric reconstructions of tomographic data naturally capture the morphology and structure, but at great computational expense when simulating heat and mass transport. A computationally efficient method is to create an abstraction of the PTL in a simple, regularized domain known as a pore-network model (PNM). This latter approach resolves the issue of computational expense, but lacks a clear relationship to the original structure and morphology of the PTL that is generally stochastic. The stochastic morphology of a PTL can be characterized using a probability distribution of void volume size, known as a pore size distribution, which is invariant with respect to sample size. Pore size distribution data can be obtained using porosimetry or tomography and is almost universally based on spherical pore volumes. This presentation discusses a methodology for transforming a spherical pore size distribution data into a pore-network model domain. This methodology maintains the appropriate stochastic distribution, physical size and bulk porosity of the original PTL. The resulting PNM domain is unique to the original PTL sample; meaning that the pore-network is material or manufacturer specific. Thus, simulation of reactant and water transport is also material or manufacturer specific. The methodology developed transforms a spherical-pore size distribution into a regularly-spaced network of pore cylinders; referred to as the pore-phase network. In order to simulate thermal transport in a PTL using the PNM architecture, the solid portion of the original material must also be transformed into a complimentary solid-phase network. The solid-phase network should also preserve the original stochastic morphology and bulk porosity of the PTL. In this methodology, the two networks (pore-phase and solid-phase) are generated independent of one another, connected only through the distribution of unit cell porosities. In this manner thermal transport through the solid-phase network can be validated independently of liquid water transport through the pore-phase network and vice-versa. When combined, the dual PNM networks capture the coupled thermal and mass transport through the PTL.

N3DFix: an Algorithm for Automatic Removal of Swelling Artifacts in Neuronal Reconstructions.

It is well established that not only electrophysiology but also morphology plays an important role in shaping the functional properties of neurons. In order to properly quantify morphological features it is first necessary to translate observational histological data into 3-dimensional geometric reconstructions of the neuronal structures. This reconstruction process, independently of being manual or (semi-)automatic, requires several preparation steps (e.g. histological processing) before data acquisition using specialized software. Unfortunately these processing steps likely produce artifacts which are then carried to the reconstruction, such as tissue shrinkage and formation of swellings. If not accounted for and corrected, these artifacts can change significantly the results from morphometric analysis and computer simulations. Here we present N3DFix, an open-source software which uses a correction algorithm to automatically find and fix swelling artifacts in neuronal reconstructions. N3DFix works as a post-processing tool and therefore can be used in either manual or (semi-)automatic reconstructions. The algorithm's internal parameters have been defined using a "ground truth" dataset produced by a neuroanatomist, involving two complementary manual reconstruction procedures: in the first, neuronal topology was faithfully reconstructed, including all swelling artifacts; in the second procedure a meticulous correction of the artifacts was manually performed directly during neuronal tracing. The internal parameters of N3DFix were set to minimize the differences between manual amendments and the algorithm's corrections. It is shown that the performance of N3DFix is comparable to careful manual correction of the swelling artifacts. To promote easy access and wide adoption, N3DFix is available in NEURON, Vaa3D and Py3DN.

CALIBRATION OF A MULTI-CAMERA ROVER

Abstract. Multi-Camera-Rover are recently coming up for usual terrestrical surveying tasks. This technique is new for the surveyors. Although photogrammetric specialists realize the benefits of such systems immediately, surveyors have difficulties to find efficient usages. To approach this new measurement systems the technique has to be understood and the confidence on the accuray has to grow. In this paper we analyze the accuracy of a Multi-Camera-Rover using an indoor testfield by photogrammetric algorithms. The results show that the knowledge of the interior orientation parameter of the cameras and the relative orientation of the cameras is essential for precise geometric reconstructions. Knowing these additional data, high accurate results become possible.

CALIBRATION OF A MULTI-CAMERA ROVER

Multi-Camera-Rover are recently coming up for usual terrestrical surveying tasks. This technique is new for the surveyors. Although photogrammetric specialists realize the benefits of such systems immediately, surveyors have difficulties to find efficient usages. To approach this new measurement systems the technique has to be understood and the confidence on the accuray has to grow. In this paper we analyze the accuracy of a Multi-Camera-Rover using an indoor testfield by photogrammetric algorithms. The results show that the knowledge of the interior orientation parameter of the cameras and the relative orientation of the cameras is essential for precise geometric reconstructions. Knowing these additional data, high accurate results become possible.

Decadal‐scale changes of the ödenwinkelkees, central austria, suggest increasing control of topography and evolution towards steady state

Small mountain glaciers have short mass balance response times to climate change and are consequently very important for short‐term contributions to sea level. However, a distinct research and knowledge gap exists between (1) wider regional studies that produce overview patterns and trends in glacier changes, and (2) in situ local scale studies that emphasise spatial heterogeneity and complexity in glacier responses to climate. This study of a small glacier in central Austria presents a spatiotemporally detailed analysis of changes in glacier geometry and changes in glaciological behaviour. It integrates geomorphological surveys, historical maps, aerial photographs, airborne LiDAR data, ground‐based differential global positioning surveys and Ground Penetrating Radar surveys to produce three‐dimensional glacier geometry at 13 time increments spanning from 1850 to 2013. Glacier length, area and volume parameters all generally showed reductions with time. The glacier equilibrium line altitude increased by 90 m between 1850 and 2008. Calculations of the mean bed shear stress rapidly approaching less than 100 kPA, of the volume–area ratio fast approaching 1.458, and comparison of the geometric reconstructions with a 1D theoretical model could together be interpreted to suggest evolution of the glacier geometry towards steady state. If the present linear trend in declining ice volume continues, then the Ödenwinkelkees will disappear by the year 2040, but we conceptualise that non‐linear effects of bed overdeepenings on ice dynamics, of supraglacial debris cover on the surface energy balance, and of local topographically driven controls, namely wind‐redistributed snow deposition, avalanching and solar shading, will become proportionally more important factors in the glacier net balance.