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Mesh models generated by multi view stereo (MVS) algorithms often fail to represent in an adequate manner the sharp, natural edge details of the scene. The harsh depth discontinuities of edge regions are eventually a challenging task for dense reconstruction, while vertex displacement during mesh refinement frequently leads to smoothed edges that do not coincide with the fine details of the scene. Meanwhile, 3D edges have been used for scene representation, particularly man-made built environments, which are dominated by regular planar and linear structures. Indeed, 3D edge detection and matching are commonly exploited either to constrain camera pose estimation, or to generate an abstract representation of the most salient parts of the scene, and even to support mesh reconstruction. In this work, we attempt to jointly use 3D edge extraction and MVS mesh generation to promote edge detail preservation in the final result. Salient 3D edges of the scene are reconstructed with state-of-the-art algorithms and integrated in the dense point cloud to be further used in order to support the mesh triangulation step. Experimental results on benchmark dataset sequences using metric and appearance-based measures are performed in order to evaluate our hypothesis.

The aim of this study is to develop an automated process for modeling average 3D human body according to body types using both NUBRS-based modeling software Rhinoceros 3D® (Rhino) and Grasshopper as an algorithm editor. First, we categorized men aged 36 to 55 years included in SizeUSA 3D data into the three body types (normal, overweight, and obese), and selected seven samples in each body type. To execute the automated process of generating an average 3D model of their lower bodies in a step-by-step manner, the following procedures were performed: (1) Determine the main reference lines on the 3D-scanned lower bodies, including six horizontal reference lines and six vertical reference lines; (2) Create horizontal and vertical line grids and intersection points (3) Generate an average 3D model in a position that corresponds to the average coordinates of the intersection points (vertex coordinates) of seven samples for each body type. A Grasshopper algorithm was formulated to automatically execute all procedures that had to be repeatedly performed. As a way to verify the average model’s size and shape, the girth measurements of the samples for each body type were averaged, and the results were compared with those of the 3D average body shape. It was found that the deviation was less than 1 cm, which indicates the validity of the 3D modeling approach applied in the present study. Each process was incorporated into commands available in the Rhino interface, and this automation allowed a number of 3D body shape modeling operations to be implemented in a significantly reduced time period.

The Wiener index, due to its many applications is considered to be one of very important distance-based index. But the Padmaker-Ivan (PI) index is kind of the only distance related index linked to parallelism of edges. The PI index like other distance related indices has great disseminating power. The index was firstly investigated by Khadikar et al. (2001), they have probed the chemical applications of the PI index. They proved that the proposed PI index correlates highly with the physicochemical properties and biological activities of a large number of diverse and complex chemical compounds and the Wiener and Szeged indices. Recently, the vertex Padmarkar-Ivan (PIv) index of a chemical graph G was introduced as the sum over all edges uv of a molecular graph G of the vertices of the graph that are not equidistant to the vertices u and v. In this paper, the vertex PIv index of certain triangular tessellation are computed by using graph-theoretic analysis, combinatorial computing, and edge-dividing technology.

Diffs, a concept known from source code version control systems such as git, is interesting for geospatial, event-based workflows. We investigate how the native mathematical structure of vector geometries can be utilized in order to create a diffing algorithm tailored to geospatial vector data. Diffing algorithms are a well-researched area which dates to the 1970ies; however, we find that geospatial diffing operations tends to be carried out using generic algorithms combined with a pre- and post-processing step. We created GeomDiff, an algorithm and storage format tailored to geospatial vector data. The creation time, apply/undo time, and patch size of GeomDiff was compared to three other generic algorithms by running an online experiment using 2.5 million real-world geometry pairs from OpenStreetMap. We found that the GeomDiff algorithm performs better than or on-par with the alternatives on point-geometries, and complex geometries with a small (

In the fields of computer graphics and computer vision, a great amount of research and analysis has been conducted on expression-carrying face models. How to construct more realistic and effective 3D face models has become an immense challenge to researchers. This paper proposes a parametric 3D face model editing algorithm based on existing 3D face models. The algorithm takes a number of existing 3D face models with different expressions as input, edits the models through mostly through model deformation and interpolation, and generates a new 3D face model. In particular, the face model editing process begins with selecting multiple face models with different expressions as input. Second, with one of the selected models as the source model and others as the target models, the source model and all target models are registered one by one; meanwhile, the vertex correspondence between the registered models is established. Third, the selected 3D models are parameterized to a planar disc through quasi-conformal mapping. Fourth, relying on the vertex correspondence, a set of corresponding control points between different models are established. The model is then deformed and interpolated under the guidance of the control points and by using the quasi-conformal iteration method, which produces the 2D face models with transitional expressions between the source model and the target models. Finally, the 2D models are restored to the corresponding 3D face models using the model restoration algorithm. Additionally, this paper proposes to use the Beltrami coefficient to guide the quasi-conformal iteration in performing the mapping between two planes. This coefficient then serves as a measure to evaluate the similarity between the edited model and the original one. The proposed algorithm has been evaluated through extensive experiments. The results suggest that compared with existing editing methods, the proposed method is more effective and efficient in constructing various 3D face models.

In hair transplantation, recipient-site creation is an important step. It is a repetitive and time-consuming step, which increased the “out-of-body time” for the grafts, which could hamper their survival. To solve this problem, we had devised an instrument called the Multi Slit Knife (MSK). The MSK has advantages of creating a high-density brick pattern of recipient sites in significantly less time. It had the undesirable side effect of damaging the preexisting hair follicles while making slits in the balding region. The MSK had some limitations. It was also difficult to maneuver the MSK in the vertex region where maintaining the natural whorl pattern of hair is important to obtain optimal aesthetic results. To overcome the shortcomings of the original MSK, we made a few changes to it to make a new modified MSK. It has fewer knives and a smaller platform as compared to the original MSK, better ergonomics, and more customizability with choices for blade sizes, number, and spacing. It tries to retain the advantages of the original MSK while reducing the damage to the preexisting hairs in the recipient regions. It is also better adapted at creating the recipient sites in a whorl pattern, closely mimicking the natural direction and angles of the hair in the vertex region. The modified MSK can be used singly or in combination with the original MSK, based on the patient’s recipient areas, making it a versatile set of instrument for making multiple coronal slits for hair transplant.

In this paper we present an efficient GPU-based framework to dynamically perform the voxelization of polygonal models for training 3D convolutional neural networks. It is designed to manage the dataset augmentation by using efficient geometric transformations and random vertex displacements in GPU. With the proposed system, every voxelization is carried out on-the-fly for directly feeding the network. The computing performance with this approach is much better than with the standard method, that carries out every voxelization of each model separately and has much higher data processing overhead. The core voxelization algorithm works by using the standard rendering pipeline of the GPU. It generates binary voxels for both the interior and the surface of the models. Moreover, it is simple, concise and very compatible with commodity hardware, as it neither uses complex data structures nor needs vendor-specific hardware or additional dependencies. This framework dramatically reduces the input/output operations, and completely eliminates the storage footprint of the voxelization dataset, managing it as an implicit dataset.

In this paper, we proposed a novel operation to reconstruction tetrahedrons within a certain region, which we call MFRC (Multi-face reconstruction). During the existing tetrahedral mesh improvement methods, the flip operation is one of the very important components. However, due to the limited area affected by the flip, the improvement of the mesh quality by the flip operation is also very limited. The proposed MFRC algorithm solves this problem. MFRC can reconstruct the local mesh in a larger range and can find the optimal tetrahedron division in the target area within acceptable time complexity. Therefore, based on the MFRC algorithm, we combined other operations including smoothing, edge removal, face removal, and vertex insertion/deletion to develop an effective mesh quality improvement method. Numerical experiments of dozens of meshes show that the algorithm can effectively improve the low-quality elements in the tetrahedral mesh, and can effectively reduce the running time, which has important significance for the quality improvement of large-scale mesh.

3D morphable models are widely used for the shape representation of an object class in computer vision and graphics applications. In this work, we focus on deep 3D morphable models that directly apply deep learning on 3D mesh data with a hierarchical structure to capture information at multiple scales. While great efforts have been made to design the convolution operator, how to best aggregate vertex features across hierarchical levels deserves further attention. In contrast to resorting to mesh decimation, we propose an attention based module to learn mapping matrices for better feature aggregation across hierarchical levels. Specifically, the mapping matrices are generated by a compatibility function of the keys and queries. The keys and queries are trainable variables, learned by optimizing the target objective, and shared by all data samples of the same object class. Our proposed module can be used as a train-only drop-in replacement for the feature aggregation in existing architectures for both downsampling and upsampling. Our experiments show that through the end-to-end training of the mapping matrices, we achieve state-of-the-art results on a variety of 3D shape datasets in comparison to existing morphable models., Published in CVPR 2021

Complex 3D building models, because of their huge data volume, almost always result in transmission congestion, which leads to poor user experience. To reduce the real-time transmission pressure, a novel view-dependent progressive transmission method was developed. With this method, only a small amount of transmitted data is necessary to achieve an acceptable rendering effect when the viewpoint changes. The method involves two stages. A preprocessing stage simplifies the building model using a multi-level vertex clustering algorithm. The local mesh in each clustering unit is organized into a node tree where each node includes a vertex and its related triangles. The building model is finally reorganized into a node forest. In the reconstruction stage, all root nodes are transmitted first to build a basic model. Their descendant nodes are then requested and transmitted according to viewpoint information to refine the building model during user interaction. The experimental results show that this method can effectively improve the transmission and reconstruction efficiency of 3D building models.

Mesh reconstruction is widely used in industrial reverse engineering and other 3D scanning applications. Many of the methods used can accurately and swiftly reconstruct a model from a given input scan dataset – however, in some applications, simplification of the output mesh may be needed to render further computation tractable. This paper presents a method based on a recursive RANSAC point removal approach, where an input point cloud is deconstructed into a set of convex point clusters, each corresponding to a mesh face of the final output model. The combined use of cluster analysis and RANSAC model extraction allows the method to operate on a relatively small number of possible vertex candidates for the final mesh, leading to an output mesh with relatively few faces compared to other approaches.

When 3D scanning objects, the objective is usually to obtain a continuous surface. However, most surface scanning methods, such as structured light scanning, yield a point cloud. Obtaining a continuous surface from a point cloud requires a subsequent surface reconstruction step, which is directly affected by any error from the computation of the point cloud. In this work, we propose a one-step approach in which we compute the surface directly from structured light images. Our method minimizes the least-squares error between photographs and renderings of a triangle mesh, where the vertex positions of the mesh are the parameters of the minimization problem. To ensure fast iterations during optimization, we use differentiable rendering, which computes images and gradients in a single pass. We present simulation experiments demonstrating that our method for computing a triangle mesh has several advantages over approaches that rely on an intermediate point cloud. Our method can produce accurate reconstructions when initializing the optimization from a sphere. We also show that our method is good at reconstructing sharp edges and that it is robust with respect to image noise. In addition, our method can improve the output from other reconstruction algorithms if we use these for initialization.

Large-volume liquid scintillator detectors with ultra-low background levels have been widely used to study neutrino physics and search for dark matter. Event vertex and event time are not only useful for event selection but also essential for the reconstruction of event energy. In this study, four event vertex and event time reconstruction algorithms using charge and time information collected by photomultiplier tubes were analyzed comprehensively. The effects of photomultiplier tube properties were also investigated. The results indicate that the transit time spread is the main effect degrading the vertex reconstruction, while the effect of dark noise is limited. In addition, when the event is close to the detector boundary, the charge information provides better performance for vertex reconstruction than the time information., 11 pages, 16 figures

In this paper, we propose a novel guided normal filtering followed by vertex updating for mesh denoising. We introduce a two-stage scheme to construct adaptive consistent neighborhoods for guided normal filtering. In the first stage, we newly design a consistency measurement to select a coarse consistent neighborhood for each face in a patch-shift manner. In this step, the selected consistent neighborhoods may still contain some features. Then, a graph-cut based scheme is iteratively performed for constructing different adaptive neighborhoods to match the corresponding local shapes of the mesh. The constructed local neighborhoods in this step, known as the adaptive consistent neighborhoods, can avoid containing any geometric features. By using the constructed adaptive consistent neighborhoods, we compute a more accurate guide normal field to match the underlying surface, which will improve the results of the guide normal filtering. With the help of the adaptive consistent neighborhoods, our guided normal filtering can preserve geometric features well, and is robust against complex shapes of surfaces. Intensive experiments on various meshes show the superiority of our method visually and quantitatively.

Muons provide a clean experimental signature, typically traversing the whole experimental apparatus without decaying. Muon detection systems are therefore usually located at a rather large distance from the primary interaction vertex after all other sub-detectors. As such, experimental apparatuses at FCC-ee will certainly employ very large muon systems, covering areas of a few thousand square meters. For obvious reasons of cost, the most suitable detectors to realise these large muon systems are gas detectors. In particular, in recent years, micro-pattern gas detectors (MPGDs) have undergone very interesting developments, providing several new types of detectors with very good spatial and time resolution, high efficiency, high rate capability and high radiation tolerance. The good position and time resolution makes a MPGD an excellent particle tracker, reconstructing tracks at 4–5 m from the primary interaction vertex with sub-mm precision. Therefore MPGDs, apart from efficiently detecting muons, can precisely track and help identifying also hypothesized long lived particles (LLP) that would decay outside of the central trackers. MPGDs have the distinct advantage of being, at least for some detectors and some parts of them, mass-producible by industry, since they employ materials and manufacturing procedures that are used extensively for printed circuit boards (PCB) production. A particularly innovative MPGD, the $$\mu $$ μ RWELL, is considered as a possible candidate to build the large muon system of the IDEA detector concept for FCC-ee and is described in some more detail. Other technologies that could be considered for the realisation of muon detection systems are also briefly discussed.

The topology optimization methodology is widely applied in industrial engineering to design lightweight and efficient components. Despite that, many techniques based on structural optimization return a digital model that is far from being directly manufactured, mainly because of surface noise given by spikes and peaks on the component. For this reason, mesh post-processing is needed. Surface smoothing is one of the numerical procedures that can be applied to a triangulated mesh file to return a more appealing geometry. In literature, there are many smoothing algorithms available, but especially those based on the modification of vertex position suffer from high mesh shrinkage and loss of important geometry features like holes and surface planarity. For these reasons, an improved vertex-based algorithm based on Vollmer’s surface smoothing has been developed and introduced in this work along with two case studies included to evaluate its performances compared with existent algorithms. The innovative approach herein developed contains some sub-routines to mitigate the issues of common algorithms, and confirms to be efficient and useful in a real-life industrial context. Thanks to the developed functions able to recognize the geometry feature to be frozen during the smoothing process, the user’s intervention is not required to guide the procedure to get proper results.

Proceedings of the 29th International Workshop on Vertex Detectors (VERTEX2020) - Journal of the Physical Society of Japan, 2021. - ISBN 4-89027-147-3 - doi:10.7566/JPSCP.34.010024 International Workshop on Vertex Detectors , VERTEX2020, Tsukuba, Japan (Online), 5 Oct 2020 - 8 Oct 2020; Journal of the Physical Society of Japan, JPS Conference Proceedings 34, 010024 pp. (2021). doi:10.7566/JPSCP.34.010024, Stringent requirements are posed on the next generations of vertex and tracking detectors for high-energy physics experiments to reach the foreseen physics goals. A large variety of silicon pixel sensors targeting the specific needs of each use case are developed and tested both in laboratory and test-beam measurement campaigns. Corryvreckan is a flexible, fast and lightweight test-beam data reconstruction and analysis framework based on a modular concept of the reconstruction chain. It is designed to fulfil the requirements for offline event building in complex data-taking environments combining detectors with different readout schemes. Its modular architecture separates the framework core from the implementation of reconstruction, analysis and detector specific algorithms. In this paper, a brief overview of the software framework and the reconstruction and analysis chain is provided. This is complemented by an example analysis of a data set using the offline event building capabilities of the framework and an improved event building scheme allowing for a more efficient usage of test-beam data exploiting the pivot pixel information of the Mimosa26 sensors., Published by Journal of the Physical Society of Japan

International audience; This paper presents a reactive legged locomotion generation scheme that enables our quadruped robot CEN-TAURO to adapt to varying payloads while walking. The center-of-mass (CoM) trajectories are generated in real time in a model predictive control (MPC) fashion, trading off large stability margins against evenly stretched legs. Vertexbased zero-moment-point (ZMP) constraints are imposed to ensure quasi-static walking stability. A Kalman filter is then implemented to estimate the CoM states and the impact of external payloads which can vary online and affect/disturb the locomotion differently. The CoM estimation is used to update the MPC motion planner at every replanning instant so that the robot can react to unknown and time-varying payloads on the fly. We validate the proposed scheme through experimental trials where the robot walks on flat ground or steps on different surface levels while carrying heavy payloads. It is shown that the proposed reactive locomotion strategy enables the robot to carry 20 kg payloads, which is close to the maximum capacity of the robot arms.

The liquid-based detectors are widely used in particle and nuclear physics experiments. Due to the fixed way of constructing geometry in detector simulation such as Geant4, it is usually difficult to describe the non-uniformity of liquid in detectors. We propose a method based on GDML and tessellated detector description to share the detector geometry information between Computational Fluid Dynamics (CFD) simulation software and detector simulation software. The method makes it possible to study the impact of liquid flow and non-uniformity on some key performance of the liquid-based detectors, such as event vertex reconstruction resolution. It will also be helpful in detector design and performance optimization., 10 pages, 18 figures

Wayfinding and navigation can present substantial challenges to visually impaired (VI) people. Some of the significant aspects of these challenges arise from the difficulty of knowing the location of a moving person with enough accuracy. Positioning and localization in indoor environments require unique solutions. Furthermore, positioning is one of the critical aspects of any navigation system that can assist a VI person with their independent movement. The other essential features of a typical indoor navigation system include pathfinding, obstacle avoidance, and capabilities for user interaction. This work focuses on the positioning of a VI person with enough precision for their use in indoor navigation. We aim to achieve this by utilizing only the capabilities of a typical smartphone. More specifically, our proposed approach is based on the use of the accelerometer, gyroscope, and magnetometer of a smartphone. We consider the indoor environment to be divided into microcells, with the vertex of each microcell being assigned two-dimensional local coordinates. A regression-based analysis is used to train a multilayer perceptron neural network to map the inertial sensor measurements to the coordinates of the vertex of the microcell corresponding to the position of the smartphone. In order to test our proposed solution, we used IPIN2016, a publicly-available multivariate dataset that divides the indoor environment into cells tagged with the inertial sensor data of a smartphone, in order to generate the training and validating sets. Our experiments show that our proposed approach can achieve a remarkable prediction accuracy of more than 94%, with a 0.65 m positioning error.

This paper introduces Neural Subdivision, a novel framework for data-driven coarse-to-fine geometry modeling. During inference, our method takes a coarse triangle mesh as input and recursively subdivides it to a finer geometry by applying the fixed topological updates of Loop Subdivision, but predicting vertex positions using a neural network conditioned on the local geometry of a patch. This approach enables us to learn complex non-linear subdivision schemes, beyond simple linear averaging used in classical techniques. One of our key contributions is a novel self-supervised training setup that only requires a set of high-resolution meshes for learning network weights. For any training shape, we stochastically generate diverse low-resolution discretizations of coarse counterparts, while maintaining a bijective mapping that prescribes the exact target position of every new vertex during the subdivision process. This leads to a very efficient and accurate loss function for conditional mesh generation, and enables us to train a method that generalizes across discretizations and favors preserving the manifold structure of the output. During training we optimize for the same set of network weights across all local mesh patches, thus providing an architecture that is not constrained to a specific input mesh, fixed genus, or category. Our network encodes patch geometry in a local frame in a rotation- and translation-invariant manner. Jointly, these design choices enable our method to generalize well, and we demonstrate that even when trained on a single high-resolution mesh our method generates reasonable subdivisions for novel shapes., 16 pages

CLIC is a proposed linear $e^+e^-$ collider with center-of-mass energies of up to 3 TeV. Its main objectives are precise top quark, Higgs boson and Beyond Standard Model physics. In addition to spatial resolutions of a few micrometers and a very low material budget, the vertex and tracking detectors also require timing capabilities with a precision of a few nanoseconds to allow suppression of beam-induced background particles. Different technologies using hybrid silicon detectors are explored for the vertex detectors, such as dedicated 65 nm readout ASICs, small-pitch sensors as well as bonding using anisotropic conductive films. Monolithic sensors are the current choice for the tracking detector, and a prototype using a 180 nm high-resistivity CMOS process has been designed and produced, and is currently under evaluation. Different designs using a silicon-on-insulator process are under investigation for both vertex and tracking detector. All prototypes are tested in laboratory and beam tests, and newly developed simulation tools combining Geant4 and TCAD are used to assess and optimize their performance. This contribution gives an overview of the R&D program for the CLIC vertex and tracking detectors, highlighting new results from the prototypes., VERTEX2019 proceedings, 10 pages, 6 figures

The Heavy Photon Search (HPS) is an experiment at the Thomas Jefferson National Accelerator Facility (JLab) designed to search for a hidden sector photon (A’) in fixed-target electro-production. It uses a silicon microstrip tracking and vertexing detector placed inside a dipole magnet to measure charged particle trajectories and a fast lead-tungstate crystal calorimeter located just downstream of the magnet to provide a trigger and to identify electromagnetic showers. The HPS experiment uses both invariant mass and secondary vertex signatures to search for the A’. The experimental collaboration is small and quite heterogeneous: it is composed of members of the nuclear physics as well as particle physics communities, from universities and national labs from around the US and Europe. Enabling such a disparate group to concentrate on the physics aspects of the experiment required that the software be easy to install and use, and having such limited manpower meant that existing solutions had to be exploited.HPS has successfully completed two engineering runs and completed its first physics run in the summer of 2019. We begin with an overview of the physics goals of the experiment followed by a short description of the detector design. We then describe the software tools used to design the detector layout and simulate the expected detector performance. Event reconstruction involving track, cluster and vertex finding and fitting for both simulated and real data was, to first order, adopted from existing software originally developed for Linear Collider studies. Bringing it all together into a cohesive whole involved the use of multiple software solutions with common interfaces.

In the intelligent transportation system, the license information can be automatically recognized by the computer and the vehicle can be tracked. Red light running, illegal change of lanes, vehicle retrograde, and other illegal driving events are reasonably recorded. This is undoubtedly an effective help for the traffic police to relieve the huge work pressure. However, in China, a considerable number of vehicle tracking methods have certain limitations in resisting complex external environmental influences. The external environmental factors include but not limited to variable factors such as camera movement, jitter, and severe rain and snow. These factors cannot be controlled well, so the tracking accuracy is greatly reduced. In regard to this, this paper proposes an optimization method for moving vehicle tracking based on SPF. First, according to the size of the overlapping area of the motion area between the two images, the researcher can construct and simplify the vertex adjacency matrix that reflects the characteristics of the undirected bipartite graph. Then according to the corresponding relationship between the vertex adjacency matrix and the regional behavior and vehicle behavior, the researcher completes the regional behavior analysis and vehicle behavior analysis. On this basis, a particle filter vehicle tracking algorithm based on segmentation compensation is introduced, and the vector sum of the tracked segmentation area is used as the final position of the target vehicle. In this way, as many scattered particles fall on the target area as possible, which will greatly improve the efficiency of particle utilization, enhance tracking accuracy, and avoid the problem of tracking failure caused by too fast vehicle movement. Through experimental simulation, it can be seen that the method proposed in this paper can greatly enhance the vehicle tracking ability when tracking vehicles in “complex environments.”

Vertex concavity-convexity detection for spatial objects is a basic algorithm of computer graphics, as well as the foundation for the implementation of other graphics algorithms. In recent years, the importance of the vertex concavity-convexity detection algorithm for three-dimensional (3D) spatial objects has been increasingly highlighted, with the development of 3D modeling, artificial intelligence, and other graphics technologies. Nonetheless, the currently available vertex concavity-convexity detection algorithms mostly use two-dimensional (2D) polygons, with limited research on vertex concavity-convexity detection algorithms for 3D polyhedrons. This study investigates the correlation between the outer product and the topology of the spatial object based on the unique characteristic that the outer product operation in the geometric algebra has unified and definitive geometric implications in space, and with varied dimensionality. Moreover, a multi-dimensional unified vertex concavity-convexity detection algorithm framework for spatial objects is proposed, and this framework is capable of detecting vertex concavity-convexity for both 2D simple polygons and 3D simple polyhedrons.

Sometimes it is necessary to know the transformation to apply to a mapping shape in order to locate its true place. Such an operation can be computed if a corresponding reference object exists and we can identify corresponding points in both shapes. Nevertheless our approach does not need to match any corresponding point beforehand. The method proposed defines a polygon in the frequency domain&mdash, two periodic functions are derived from a polygonal or polygon. According to the theory of elliptic Fourier descriptors those two periodic functions can be expressed by Fourier expansions. The transformation can be computed using the coefficients of the harmonics from the corresponding shapes without taking into account where each polygon vertex is placed in the spatial domain. The transformation parameters will be derived by a least squares approach. The geomatics and geosciences applications of this method go from photogrammetry, geographic information system, computer vision, to cadaster and real estates.

International audience; For the 12 GeV upgrade of Jefferson Laboratory, a Silicon Vertex Tracker (SVT) has been designed for the CLAS12 spectrometer using single-sided microstrip sensors fabricated by Hamamatsu Photonics. The sensors have a graded angle design to minimize dead areas and a readout pitch of 156μm , with intermediate strips. Each double-sided SVT module hosts three daisy-chained sensors on each side with a full strip length of 33 cm. There are 512 channels per module, read out by four Fermilab Silicon Strip Readout (FSSR2) chips, featuring data-driven architecture, mounted on a rigid–flex hybrid board. The modules are assembled in a barrel configuration using a unique cantilevered geometry to minimize the amount of material in the tracking volume. This paper is focused on the design, qualification of the performance, and experience in operating and commissioning the tracker during the first year of the data taking.

The new Vertex Locator for LHCb, comprising a new pixel detector and readout electronics, will be installed in 2020 for data-taking in Run 3 at the LHC. The electronics centres around the "VeloPix" ASIC at the front-end operating in a triggerless readout at 40 MHz. Custom serialisers send zero-suppressed data from the VeloPix at a line rate of 5.13 Gb/s. System tests of the com- plete electronic and optical chain, along with early results from high-speed link tests at CERN are presented.

International audience; Digital light processing technique was applied to manufacture alumina ceramic parts with two types of lattice structure units, i.e. vertex interconnect structure and edge structure. The internal porosity of the unit is 40%. The printed parts were sintered and the grain size is about 1.1 μm. The bending strength of the vertex interconnect structure is much larger than that of the edge structure. Materials genome initiative (MGI) aims to digital design and intelligent manufacture for advanced components. This research shows us an example to achieve this goal.

Virtual hand usually simulates human hands by mapping the actual shapes of hands to virtual environment and modeling the hand-object manipulations in human machine interactions. For describing virtual hand and its manipulation in a unified framework, a method based on conformal geometric algebra (CGA) is proposed to solve the problems of virtual hand modeling and interaction in this paper. With the vertex blending based on CGA, the artifacts on the finger joints are improved, which enhances the realism of the virtual hand model. With the same tool, the collision detection between the virtual hand and the manipulated objects is implemented. The gesture of grasp, pinch, and hold are recognized, and the corresponding manipulation rules are established by CGA calculation. To test these three typical manipulations, the manipulated objects are imported and the manipulation effectiveness is evaluated.

We propose a new tetrahedral meshing method, fTetWild, to convert triangle soups into high-quality tetrahedral meshes. Our method builds on the TetWild algorithm, replacing the rational triangle insertion with a new incremental approach to construct and optimize the output mesh, interleaving triangle insertion and mesh optimization. Our approach makes it possible to maintain a valid floating-point tetrahedral mesh at all algorithmic stages, eliminating the need for costly constructions with rational numbers used by TetWild, while maintaining full robustness and similar output quality. This allows us to improve on TetWild in two ways. First, our algorithm is significantly faster, with running time comparable to less robust Delaunay-based tetrahedralization algorithms. Second, our algorithm is guaranteed to produce a valid tetrahedral mesh with floating-point vertex coordinates, while TetWild produces a valid mesh with rational coordinates which is not guaranteed to be valid after floating-point conversion. As a trade-off, our algorithm no longer guarantees that all input triangles are present in the output mesh, but in practice, as confirmed by our tests on the Thingi10k dataset, the algorithm always succeeds in inserting all input triangles.

The High-Luminosity Large Hadron Collider (HL-LHC) aims to increase the LHC data-set by an order of magnitude in order to increase its potential for discoveries. The high pileup at the HL-LHC presents a highly challenging environment to particle detectors. To cope with this, the current Inner Detector of the ATLAS experiment will be replaced with a new all-silicon Inner Tracker (ITk). The expected tracking performance of the ITk is presented and impact of the tracking performance on vertex reconstruction, jet flavour tagging and pileup jet rejection is shown. These studies were performed for two possible options of the pixel sensor pitch.

The accuracy of the LHCb Vertex Locator (VELO) position has ensured excellent detector performance, with a track reconstruction efficiency above 98\%, and a vertex resolution along the beam axis of about 70 $\mu$m. The real-time alignment and calibration procedure developed by the LHCb experiment for Run 2 (2015-2018) for the full detector, including the VELO, provided extremely stable conditions during the full data taking period. In 2010, a significant shrinkage of the VELO modules was observed at the operating temperature of -30 degrees with respect to survey measurements made at ambient temperature. This has been confirmed by the following laboratory measurements of different tmeperatures on a single module. In a recent study, using a dedicated LHCb data sample taken over a range of VELO temperatures, the variation of the detector position as a function of temperature has been evaluated. An overview of the VELO alignment procedure and its performance during Run 2 will be presented, with an emphasis on the study of the temperature dependence.

Constructing a robust and discriminative local descriptor for 3D shape is a key component of many computer vision applications. Although existing learning-based approaches can achieve good performance in some specific benchmarks, they usually fail to learn enough information from shapes with different shape types and structures (e.g., spatial resolution, connectivity, transformations, etc.) Focusing on this issue, in this paper, we present a more discriminative local descriptor for deformable 3D shapes with incompatible structures. Based on the spectral embedding using the Laplace-Beltrami framework on the surface, we first construct a novel local spectral feature which shows great resilience to change in mesh resolution, triangulation, transformation. Then the multi-scale local spectral features around each vertex are encoded into a `geometry image', called vertex spectral image, in a very compact way. Such vertex spectral images can be efficiently trained to learn local descriptors using a triplet neural network. Finally, for training and evaluation, we present a new benchmark dataset by extending the widely used FAUST dataset. We utilize a remeshing approach to generate modified shapes with different structures. We evaluate the proposed approach thoroughly and make an extensive comparison to demonstrate that our approach outperforms recent state-of-the-art methods on this benchmark.

With the rapid development of the economy, urgent needs for 3-D Geographical Information System (GIS) have sprung up in many application fields. The precise expression of three-dimensional topological relations is the foundation of spatial analysis, topological query, and spatial reasoning in three-dimensional space. In this paper, we subdivide the topological part &ldquo, boundary&rdquo, into face, edge, and vertex and propose a 25-intersection model (25IM) to represent topological relations between two simple spatial objects (point, line, region, and body) in 3-D space. An object in the 25IM has five topological parts: vertex, edge, face, interior, and exterior. The classification of topological relations is simplified by merging contain/inside and cover/coveredby. The 25IM describes ten groups of topological relations: body/body, body/region, body/line, body/point, region/region, region/line, region/point, line/line, line/point, and point/point. The 25IM is demonstrated to be more expressive than the 9IM and the DE-9IM, especially in distinguishing the detail situations when one object meets/covers another object (e.g., two bodies meet/cover at vertex, edge, or face).

The design of a natural gas pipeline route is a very important stage in Natural Gas Transmission Pipeline projects. It is a very complicated process requiring many different criteria for various areas to be evaluated simultaneously. These criteria include geographical, social, economic, and environmental aspects with their obstacles. In the classical approach, the optimum route design is usually determined manually with gathering the spatial references for suitable places and obstructions from the ground. This traditional method is not effective because it does not consider all the factors that affect the route of the pipeline. Today, the powerful tools incorporated in Geographical Information Systems (GIS) can be used to automatically determine the optimum route. An automatic pipeline route finder algorithm can calculate the best convenient route avoiding geographic and topological obstructs and selecting suitable places depending on their weights. In this study, an automatic natural gas pipeline design study was carried out in the east western region of Turkey. At the end of the study, an automatic natural gas pipeline route was determined using GIS and a least cost path algorithm, and an alternative study was conducted using a traditional method. In addition, a cartographic line simplification process with a point removal algorithm was used to eliminate the high vertex points and a simplified route was determined. The results were compared with the results of a finished Muş natural gas project constructed by The Turkish Petroleum Pipeline Corporation (BOTAŞ) and the negative and positive effects were evaluated. It was concluded that the use of GIS capabilities and the lowest cost path distance algorithm resulted in a 20% reduction of the cost through the simplification.

We present a carefully designed, systematic study of the angular resolution dependence of simulations with the Prometheus-Vertex neutrino-hydrodynamics code. Employing a simplified neutrino heating-cooling scheme in the Prometheus hydrodynamics module allows us to sample the angular resolution between 4 degrees and 0.5 degrees. With a newly-implemented static mesh refinement (SMR) technique on the Yin-Yang grid, the angular coordinates can be refined in concentric shells, compensating for the diverging structure of the spherical grid. In contrast to previous studies with Prometheus and other codes, we find that higher angular resolution and therefore lower numerical viscosity provides more favorable explosion conditions and faster shock expansion. We discuss the possible reasons for the discrepant results. The overall dynamics seem to converge at a resolution of about 1 degree. Applying the SMR setup to marginally exploding progenitors is disadvantageous for the shock expansion, however, because kinetic energy of downflows is dissipated to internal energy at resolution interfaces, leading to a loss of turbulent pressure support and a steeper temperature gradient. We also present a way to estimate the numerical viscosity on grounds of the measured turbulent kinetic-energy spectrum, leading to smaller values that are better compatible with the flow behavior witnessed in our simulations than results following calculations in previous literature. Interestingly, the numerical Reynolds numbers in the turbulent, neutrino-heated postshock layer (some 10 to several 100) are in the ballpark of expected neutrino-drag effects on the relevant length scales in the turbulent postshock layer. We provide a formal derivation and quantitative assessment of the neutrino drag terms in an appendix., 37 pages, 14 figures, 4 tables; revised version with neutrino drag discussion extended for numerical evaluation; accepted by ApJ

Due to recent advances in the field of virtual reality, the demand for immersive sound design has increased dramatically. While pre-recorded samples are a popular tool in this context, it has limited flexibility and user interactivity. We propose a real-time method that can synthesize fully immersive sounds of droplets falling in water. The physics of air bubbles produced in the liquid are considered in detail, and the sound samples are synthesized in a GLSL shader to make full use of parallel computing. A vertex shader shows the resulting disturbance on the liquid surface, to further immerse the user with consistent visuals. Results show that a large amount of bubbles can easily be generated on a regular desktop computer.

In this paper, we present a novel strategy to design disentangled 3D face shape representation. Specifically, a given 3D face shape is decomposed into identity part and expression part, which are both encoded and decoded in a nonlinear way. To solve this problem, we propose an attribute decomposition framework for 3D face mesh. To better represent face shapes which are usually nonlinear deformed between each other, the face shapes are represented by a vertex based deformation representation rather than Euclidean coordinates. The experimental results demonstrate that our method has better performance than existing methods on decomposing the identity and expression parts. Moreover, more natural expression transfer results can be achieved with our method than existing methods., 15 pages, 8 figures. CVPR 2019

This work provides a systematic understanding of the requirements of live 3D mesh coding, targeting (tele-)immersive media streaming applications. We thoroughly benchmark in rate-distortion and runtime performance terms, four static 3D mesh coding solutions that are openly available. Apart from mesh geometry and connectivity, our analysis includes experiments for compressing vertex normals and attributes, something scarcely found in literature. Additionally, we provide a theoretical model of the tele-immersion pipeline that calculates its expected frame-rate, as well as lower and upper bounds for its end-to-end latency. In order to obtain these measures, the theoretical model takes into account the compression performance of the codecs and some indicative network conditions. Based on the results we obtained through our codec benchmarking, we used our theoretical model to calculate and provide concrete measures for these tele-immersion pipeline’s metrics and discuss on the optimal codec choice depending on the network setup. This offers deep insight into the available solutions and paves the way for future research.

International audience; We extend the formulation of position-based rods to include elastic volumetric deformations. We achieve this by introducing an additional degree of freedom per vertex-isotropic scale (and its velocity). Including scale enriches the space of possible deformations, allowing the simulation of volumetric effects, such as a reduction in cross-sectional area when a rod is stretched. We rigorously derive the continuous formulation of its elastic energy potentials, and hence its associated position-based dynamics (PBD) updates to realize this model, enabling the simulation of up to 26000 DOFs at 140 Hz in our GPU implementation. We further show how rods can provide a compact alternative to tetrahedral meshes for the representation of complex muscle deformations, as well as providing a convenient representation for collision detection. This is achieved by modeling a muscle as a bundle of rods, for which we also introduce a technique to automatically convert a muscle surface mesh into a rods-bundle. Finally, we show how rods and/or bundles can be skinned to a surface mesh to drive its deformation, resulting in an alternative to cages for real-time volumetric deformation. The source code of our physics engine will be openly available.

Reconstruction of potential ultra-high-energy (UHE) neutrino events at the Askaryan Radio Array (ARA) is complicated by the variable index of refraction of South Pole ice, leading to curved radio signal paths from the interaction vertex. Using a spline table framework for fast raytracing approximation, we perform a GPU-accelerated interferometric reconstruction of the event vertex. We also demonstrate how use of both direct and reflected/refracted radio signals can allow reconstruction of the distance to the interaction vertex, an important step towards neutrino energy reconstruction.

With cardiovascular disease (CVD) remaining the primary cause of death worldwide, early detection of CVDs becomes essential. The intracardiac flow is an important component of ventricular function, motion kinetics, wash-out of ventricular chambers, and ventricular energetics. Coupling between Computational Fluid Dynamics (CFD) simulations and medical images can play a fundamental role in terms of patient-specific diagnostic tools. From a technical perspective, CFD simulations with moving boundaries could easily lead to negative volumes errors and the sudden failure of the simulation. The generation of high-quality 4D meshes (3D in space + time) with 1-to-1 vertex becomes essential to perform a CFD simulation with moving boundaries. In this context, we developed a semiautomatic morphing tool able to create 4D high-quality structured meshes starting from a segmented 4D dataset. To prove the versatility and efficiency, the method was tested on three different 4D datasets (Ultrasound, MRI, and CT) by evaluating the quality and accuracy of the resulting 4D meshes. Furthermore, an estimation of some physiological quantities is accomplished for the 4D CT reconstruction. Future research will aim at extending the region of interest, further automation of the meshing algorithm, and generating structured hexahedral mesh models both for the blood and myocardial volume.

The availability of affordable 3D full body reconstruction systems has given rise to free-viewpoint video (FVV) of human shapes. Most existing solutions produce temporally uncorrelated point clouds or meshes with unknown point/vertex correspondences. Individually compressing each frame is ineffective and still yields to ultra-large data sizes. We present an end-to-end deep learning scheme to establish dense shape correspondences and subsequently compress the data. Our approach uses sparse set of "panoramic" depth maps or PDMs, each emulating an inward-viewing concentric mosaics. We then develop a learning-based technique to learn pixel-wise feature descriptors on PDMs. The results are fed into an autoencoder-based network for compression. Comprehensive experiments demonstrate our solution is robust and effective on both public and our newly captured datasets., 10 pages, 12 figures, CVPR 2018 paper

International audience; This paper shows an application of a vertex-based Compatible Discrete Operator (CDO) scheme to simulate the Richards equation on meshes using polyhedral cells. Second order spatial accuracy is reached for a verification test case using two meshes made of different types of polyhedral cells. A second validation test case dealing with a variably saturated soil inside a vertical column has been simulated, with three advected passive pollutants being released. Results are in good agreement with the reference for both types of mesh. MPI scalability has also been assessed at scale up to 98,304 cores of a Cray X30 for a 1.7 B cell mesh for the simulation of the aforementioned case, and nearly linear speed-up is observed. Finally the implementation of hybrid MPI-OpenMP has been tested on 2 types of Intel Xeon Phi Knights Landing co-processors, showing that the best configuration for the code is obtained when all the physical cores are filled by MPI tasks and the 4 hyperthreads by OpenMP threads.

In this work, a fast method of vertex reconstructing for incident ions in GEM detectors was proposed. As inspired by the Time Projection Chamber (TPC), the time information of the consecutive signal samples from Front End Electronics (FEE) was employed. To demonstrate the method, an experiment involving a 2D-readout THGEM detector with an APV-25 FEE was taken. With one experiment dependent parameter in the analysis, the proposed method led to a spatial resolution of 0.45 mm, compared with the same number of 9.10 mm from the traditional center of gravity method.

In this paper, we propose the first sketching system for interactively personalized and photorealistic face caricaturing. Input an image of a human face, the users can create caricature photos by manipulating its facial feature curves. Our system firstly performs exaggeration on the recovered 3D face model according to the edited sketches, which is conducted by assigning the laplacian of each vertex a scaling factor. To construct the mapping between 2D sketches and a vertex-wise scaling field, a novel deep learning architecture is developed. With the obtained 3D caricature model, two images are generated, one obtained by applying 2D warping guided by the underlying 3D mesh deformation and the other obtained by re-rendering the deformed 3D textured model. These two images are then seamlessly integrated to produce our final output. Due to the severely stretching of meshes, the rendered texture is of blurry appearances. A deep learning approach is exploited to infer the missing details for enhancing these blurry regions. Moreover, a relighting operation is invented to further improve the photorealism of the result. Both quantitative and qualitative experiment results validated the efficiency of our sketching system and the superiority of our proposed techniques against existing methods., 12 pages,16 figures,submitted to IEEE TVCG

The automatic reconstruction of three-dimensional particle tracks from Active Target Time Projection Chambers data can be a challenging task, especially in the presence of noise. In this article, we propose a non-parametric algorithm that is based on the idea of clustering point triplets instead of the original points. We define an appropriate distance measure on point triplets and then apply a single-link hierarchical clustering on the triplets. Compared to parametric approaches like RANSAC or the Hough transform, the new algorithm has the advantage of potentially finding trajectories even of shapes that are not known beforehand. This feature is particularly important in low-energy nuclear physics experiments with Active Targets operating inside a magnetic field. The algorithm has been validated using data from experiments performed with the Active Target Time Projection Chamber developed at the National Superconducting Cyclotron Laboratory (NSCL).The results demonstrate the capability of the algorithm to identify and isolate particle tracks that describe non-analytical trajectories. For curved tracks, the vertex detection recall was 86\% and the precision 94\%. For straight tracks, the vertex detection recall was 96\% and the precision 98\%. In the case of a test set containing only straight linear tracks, the algorithm performed better than an iterative Hough transform., 12 pages; fixed up references

Media, image processing, and geometric-based systems and applications need data structures to model and represent different geometric entities and objects. These data structures have to be time efficient and compact in term of space. Many structures in use are proposed to satisfy those constraints. This paper introduces a novel compact data structure inspired by the XOR-linked lists. The subject of this paper concerns the triangular data structures. Nevertheless, the underlying idea could be used for any other geometrical subdivision. The ability of the bitwise XOR operator to reduce the number of references is used to model triangle and vertex references. The use of the XOR combined references needs to define a context from which the triangle is accessed. The direct access to any triangle is not possible using only the XOR-linked scheme. To allow the direct access, additional information are added to the structure. This additional information permits a constant time access to any element of the triangulation using a local resolution scheme. This information represents an additional cost to the triangulation, but the gain is still maintained. This cost is reduced by including this additional information to a local sub-triangulation and not to each triangle. Sub-triangulations are calculated implicitly according to the catalog-based structure. This approach could be easily extended to other representation models, such as vertex-based structures or edge-based structures. The obtained results are very interesting since the theoretical gain is estimated to 38 % and the practical gain obtained from sample benches is about 34 %.

Compute-mode rendering is becoming more and more attractive for non-standard rendering applications, due to the high flexibility of compute-mode execution. These newly designed pipelines often include streaming vertex and geometry processing stages. In typical triangle meshes, the same transformed vertex is on average required six times during rendering. To avoid redundant computation, a post-transform cache is traditionally suggested to enable reuse of vertex processing results. However, traditional caching neither scales well as the hardware becomes more parallel, nor can be efficiently implemented in a software design. We investigate alternative strategies to reusing vertex shading results on-the-fly for massively parallel software geometry processing. Forming static and dynamic batching on the data input stream, we analyze the effectiveness of identifying potential local reuse based on sorting, hashing, and efficient intra-thread-group communication. Altogether, we present four vertex reuse strategies, tailored to modern parallel architectures. Our simulations showcase that our batch-based strategies significantly outperform parallel caches in terms of reuse. On actual GPU hardware, our evaluation shows that our strategies not only lead to good reuse of processing results, but also boost performance by $2-3\times$ compared to na\"ively ignoring reuse in a variety of practical applications.