Axis Representation Research Articles

Point2MM: Learning medial mesh from point clouds

Medial mesh is the most commonly used representation of medial axis transform (MAT) which is a high-fidelity compact representation of 3D shape. Existing learning methods of extracting medial mesh from point clouds either have strict requirements of supervising training data, or are incapable of learning the complete form of medial mesh, leading to large reconstruction error. We introduce Point2MM, an unsupervised method for learning a complete medial mesh from point clouds. Our key idea is to use the envelop geometry of medial primitives – spheres, cones, and slabs – to capture the intrinsic geometry of shape, and the connectivity of medial mesh to capture the topology of shape. We firstly predict initial medial spheres by learning the geometric transformation of point clouds, then construct an initial connectivity of the medial spheres by learning the probability of medial cones and medial slabs with a novel unsupervised formulation. Finally we propose an iterative strategy for fine-tuning medial primitives. Extensive evaluations and comparisons show our method has superior accuracy and robustness in learning medial mesh from point clouds. In addition, the excessive training time is also a concern for our research, and it is a limitation where we need to make improvements in our future work.

Spatially distributed lane planning for navigation in 3D environments

AbstractThis article introduces the new problem of planning spatially distributed lanes for supporting multi‐agent navigation applications in 3D environments. Our proposed approach computes the max‐flow of a 3D medial axis representation of the environment in order to globally compute collision‐free lanes exploring the entire free space of the volumetric scene. Our method addresses agent clearance and path dispersion in order to provide a comprehensive solution to globally compute lanes to be used by multiple agents in 3D environments. By selecting the desired lane dispersion our approach offers an intuitive and powerful way to explore variations in the computed collections of lanes. Dispersion is addressed with a combination of new techniques based on max flow computation, clearance‐based path separation, and adaptive shortcut‐based smoothing.

Laser Curve Extraction of Wheelset Based on Deep Learning Skeleton Extraction Network.

In this paper, a new algorithm for extracting the laser fringe center is proposed. Based on a deep learning skeleton extraction network, the laser stripe center can be extracted quickly and accurately. Skeleton extraction is the process of reducing the shape image to its approximate central axis representation while maintaining the image’s topological and geometric shape. Skeleton extraction is an important step in topological and geometric shape analysis. According to the characteristics of the wheelset laser curve dataset, a new skeleton extraction network, a hierarchical skeleton network (LuoNet), is proposed. The proposed architecture has three levels of the encoder–decoder network, and YE Module interconnection is designed between each level of the encoder and decoder network. In the wheelset laser curve dataset, the F1_score can reach 0.714. Compared with the traditional laser curve center extraction algorithm, the proposed LuoNet algorithm has the advantages of short running time, high accuracy, and stable extraction results.

Evaluating Data‐type Heterogeneity in Interactive Visual Analyses with Parallel Axes

AbstractThe application of parallel axes for the interactive visual analysis of multidimensional data is a widely used concept. While multidimensional data sets are commonly heterogeneous in nature, i.e. data items contain both numerical and categorical (including ordinal) attribute values, the use of parallel axes often assumes either numerical or categorical attributes. While Parallel Coordinates and their large variety of extensions focus on numerical data, Parallel Sets and related methods focus on categorical attributes. While both concepts allow for displaying heterogeneous data, no clear strategies have been defined for representing categories in Parallel Coordinates or discretization of continuous ranges in Parallel Sets. In practice, type conversion as a pre‐processing step can be used as well as coordinated views of numerical and categorical data visualizations. We evaluate traditional and state‐of‐the‐art approaches with respect to the interplay of categorical and numerical dimensions for querying probability‐based events. We also compare against a heterogeneous Parallel Coordinates/Parallel Set approach with a novel interface between categorical and numerical axes . We show that approaches for mapping categorical data to numerical axis representations can lead to lower accuracy in answering probability‐based questions and higher response times than hybrid approaches in multiple‐event scenarios.

A multisite decomposition of the tensor network path integrals.

Tensor network decompositions of path integrals for simulating open quantum systems have recently been proven to be useful. However, these methods scale exponentially with the system size. This makes it challenging to simulate the non-equilibrium dynamics of extended quantum systems coupled with local dissipative environments. In this work, we extend the tensor network path integral (TNPI) framework to efficiently simulate such extended systems. The Feynman-Vernon influence functional is a popular approach used to account for the effect of environments on the dynamics of the system. In order to facilitate the incorporation of the influence functional into a multisite framework (MS-TNPI), we combine a matrix product state (MPS) decomposition of the reduced density tensor of the system along the sites with a corresponding tensor network representation of the time axis to construct an efficient 2D tensor network. The 2D MS-TNPI network, when contracted, yields the time-dependent reduced density tensor of the extended system as an MPS. The algorithm presented is independent of the system Hamiltonian. We outline an iteration scheme to take the simulation beyond the non-Markovian memory introduced by solvents. Applications to spin chains coupled to local harmonic baths are presented; we consider the Ising, XXZ, and Heisenberg models, demonstrating that the presence of local environments can often dissipate the entanglement between the sites. We discuss three factors causing the system to transition from a coherent oscillatory dynamics to a fully incoherent dynamics. The MS-TNPI method is useful for studying a variety of extended quantum systems coupled with solvents.

Spline-based medial axis transform representation of binary images

Medial axes are well-known descriptors used for representing, manipulating, and compressing binary images. In this paper, we present a full pipeline for computing a stable and accurate piece-wise B-spline representation of Medial Axis Transforms (MATs) of binary images. A comprehensive evaluation on a benchmark shows that our method, called Spline-based Medial Axis Transform (SMAT), achieves very high compression ratios while keeping quality high. Compared with the regular MAT representation, the SMAT yields a much higher compression ratio at the cost of a slightly lower image quality. We illustrate our approach on a multi-scale SMAT representation, generating super-resolution images, and free-form binary image deformation.

Induced astigmatism biases the orientation information represented in multivariate electroencephalogram activities.

A small physical change in the eye influences the entire neural information process along the visual pathway, causing perceptual errors and behavioral changes. Astigmatism, a refractive error in which visual images do not evenly focus on the retina, modulates visual perception, and the accompanying neural processes in the brain. However, studies on the neural representation of visual stimuli in astigmatism are scarce. We investigated the relationship between retinal input distortions and neural bias in astigmatism and how modulated neural information causes a perceptual error. We induced astigmatism by placing a cylindrical lens on the dominant eye of human participants, while they reported the orientations of the presented Gabor patches. The simultaneously recorded electroencephalogram activity revealed that stimulus orientation information estimated from the multivariate electroencephalogram activity was biased away from the neural representation of the astigmatic axis and predictive of behavioral bias. The representational neural dynamics underlying the perceptual error revealed the temporal state transition; it was transiently dynamic and unstable (approximately 350 ms from stimulus onset) that soon stabilized. The biased stimulus orientation information represented by the spatially distributed electroencephalogram activity mediated the distorted retinal images and biased orientation perception in induced astigmatism.

Shape reconstruction of delamination defects using thermographic infrared signals based on an enhanced Canny approach

he Canny shape-reconstruction algorithm is combined with the thermographic signal reconstruction (TSR) technique for the characterisation of delamination defects in planar multilayer structures. The adopted approach consists in fitting the raw thermographic images to a low-degree polynomial in the log–log representation of the time axis, according to TSR technique, and then apply the Canny algorithm to the reconstruction of the original signals. The proposed juxtaposition of the two treatments benefits from the inherent signal de-noising and compression of the TSR algorithm, thus enhancing the performance of the overall reconstruction process. The proposed approach has been applied using synthetic signals obtained via a 3D semi-analytical simulation code and the obtained reconstructed images have been compared with the (known) delamination geometry demonstrating satisfactory results.

Virtual reality framework for editing and exploring medial axis representations of nanometric scale neural structures

We present a novel virtual reality (VR) based framework for the exploratory analysis of nanoscale 3D reconstructions of cellular structures acquired from rodent brain samples through serial electron microscopy. The system is specifically targeted on medial axis representations (skeletons) of branched and tubular structures of cellular shapes, and it is designed for providing to domain scientists: i) effective and fast semi-automatic interfaces for tracing skeletons directly on surface-based representations of cells and structures, ii) fast tools for proofreading, i.e., correcting and editing of semi-automatically constructed skeleton representations, and iii) natural methods for interactive exploration, i.e., measuring, comparing, and analyzing geometric features related to cellular structures based on medial axis representations. Neuroscientists currently use the system for performing morphology studies on sparse reconstructions of glial cells and neurons extracted from a sample of the somatosensory cortex of a juvenile rat. The framework runs in a standard PC and has been tested on two different display and interaction setups: PC-tethered stereoscopic head-mounted display (HMD) with 3D controllers and tracking sensors, and a large display wall with a standard gamepad controller. We report on a user study that we carried out for analyzing user performance on different tasks using these two setups.

CrossVis: A visual analytics system for exploring heterogeneous multivariate data with applications to materials and climate sciences

We present a new visual analytics system, called CrossVis, that allows flexible exploration of multivariate data with heterogeneous data types. After presenting the design requirements, which were derived from prior collaborations with domain experts, we introduce key features of CrossVis beginning with a tabular data model that coordinates multiple linked views and performance enhancements that enable scalable exploration of complex data. Next, we introduce extensions to the parallel coordinates plot, which include new axis representations for numerical, temporal, categorical, and image data, an embedded bivariate axis option, dynamic selections, focus+context axis scaling, and graphical indicators of key statistical values. We demonstrate the practical effectiveness of CrossVis through two scientific use cases; one focused on understanding neural network image classifications from a genetic engineering project and another involving general exploration of a large and complex data set of historical hurricane observations. We conclude with discussions regarding domain expert feedback, future enhancements to address limitations, and the interdisciplinary process used to design CrossVis.

A total Lagrangian Timoshenko beam formulation for geometrically nonlinear isogeometric analysis of planar curved beams

This paper presents a new total Lagrangian Timoshenko beam formulation with the isogeometric analysis approach for a geometrically nonlinear analysis of planar curved beams. The proposed formulation is derived from the two-dimensional continuum theory, and a beam configuration is characterized by the beam axis and the director vectors of cross sections. Non-uniform rational B-spline (NURBS) curves are used for the geometric representation of the beam axis and the discretization of the unknown kinematics, i.e., the translational displacements of the beam axis and the cross-sectional rotation angle. Several well-established examples covering the analysis of many types of beam, i.e., straight, curved, and free-form beams with varying curvature, are considered. The obtained results by the proposed formulation are compared with those in the literature, and the accuracy and efficiency of the proposed formulation are assessed. The prominent properties of using NURBS curves in analysis, i.e., effective reduction in locking effects, higher accuracy per degree-of-freedom, and better geometric representations, are also verified for the proposed beam formulation.

Kinematic Sensitivity Analysis and Dimensional Synthesis of a Redundantly Actuated Parallel Robot for Friction Stir Welding

Friction stir welding (FSW) has been widely applied in many fields as an alternative to traditional fusion welding. Although serial robots can provide the orientation capability required to weld along curved surfaces, they cannot adequately support the huge axial downward forces that FSW generates. Available parallel mechanism architectures, particularly redundantly actuated architectures for FSW, are still very limited. In this paper, a redundantly actuated 2UPR-2RPU parallel robot for FSW is proposed, where U denotes a universal joint, R denotes a revolute joint and P denotes a prismatic pair. First, its semi-symmetric structure is described. Next, inverse kinematics analysis involving an analytical representation of rotational axes is implemented. Velocity analysis is also conducted, which leads to the formation of a Jacobian matrix. Sensitivity performance is evaluated utilizing level set and convex optimization methods, where the local sensitivity indices are unit consistent, coordinate free, and of definite physical significance. Furthermore, global and hierarchical sensitivity indices are proposed for the design process. Finally, dimension synthesis is conducted based on the sensitivity indices and the optimal link parameters of the parallel robot are obtained. In summary, this paper proposes a dimensional synthesis method for a redundantly actuated parallel robot for FSW based on sensitivity indices.

Revisiting the medial axis for planar shape decomposition

We present a simple computational model for planar shape decomposition that naturally captures most of the rules and salience measures suggested by psychophysical studies, including the minima and short-cut rules, convexity, and symmetry. It is based on a medial axis representation in ways that have not been explored before and sheds more light into the connection between existing rules like minima and convexity. In particular, vertices of the exterior medial axis directly provide the position and extent of negative minima of curvature, while a traversal of the interior medial axis directly provides a small set of candidate endpoints for part-cuts. The final selection follows a prioritized processing of candidate part-cuts according to a local convexity rule that can incorporate arbitrary salience measures. Neither global optimization nor differentiation is involved. We provide qualitative and quantitative evaluation and comparisons on ground-truth data from psychophysical experiments. With our single computational model, we outperform even an ensemble method on several other competing models.

Influence of the Diameter of Grasped Spheres on the Rotation Angle and Axis of the Second to Fifth Carpometacarpal Joints

While previous studies have investigated the range of motion of the carpometacarpal (CMC) joints, there have been no results reported regarding the effects of the size of the grasped object. Therefore, we used a finite helical axis representation to investigate the rotation angles and rotation axes of the second to fifth CMC joints when three spheres with different diameters were grasped. Nine Japanese men were selected. Three-dimensional bone models were constructed based on cross-sectional images of the hand using X-ray computed tomography. Imaging was conducted under four conditions: a baseline posture without holding a sphere and postures in which three spheres with different diameters (table tennis ball: 40-mm; tennis ball: 67-mm; softball: 97-mm) were grasped. For all grasped spheres, the rotation angle was smallest for the third CMC joint and largest for the fifth CMC joint. Rotation angles were almost the same for all CMC joints regardless of the size of the grasped sphere. To quantitatively evaluate rotation axes, the angle created with the Z-axis (radioulnar axis) when the rotation axis was projected on the YZ plane (coronal plane) was defined as α (− 90° < α ≤ 90°). For the rotational axis, α angles of the second and fifth CMC joints tended to decrease as the diameter of the grasped sphere increased. Results demonstrated that in the spheres examined in the present study, CMC joint rotation axes rather than angles changed in response to differences in sphere size.

Axes of Real-World Objects: Evidence from Orientation Reflection Errors

Theories of visual object representation often assume that object shapes are represented with respect to a set of internal axes. However, few studies have examined how object axes are defined. Research has suggested that the axes of a simple elongated object (e.g., pen) are defined by the object's elongation (e.g., Sekuler & Swimmer, 2000). But what about the axes of objects that have a side protrusion (e.g., hatchet), or those that possess two equally-elongated parts (e.g., boomerang)? We probed the axes underlying representations of real-world objects in three shape categories: I-shaped, L-shaped, and V-shaped (Fig. 1). We adopted a novel task paradigm that involved analyzing participants' errors in an orientation recall task. Participants viewed an object at a random orientation, and later attempted to reproduce the object's orientation. Previous studies have shown that errors in this task often take the form of reflections across an object axis (e.g., Gregory & McCloskey, 2010). By identifying the reflection axes in participants' reflection errors (Fig.2), we inferred the axes for different shapes of objects. For all three types of stimuli, we consistently observed a pair of perpendicular reflection axes related to salient geometric properties of the objects (Fig.3). For 'I' objects, the axes were defined according to shape elongation, consistent with previous findings. For 'L' objects, the axes were defined by the objects' elongated part (e.g., hatchet's handle), independent of the protrusion (hatchet's blade). For 'V' objects, the axes were defined according to the line that partitions the objects into symmetrical halves. We discuss the implications of these findings for proposals concerning object axis representation. We suggest that our results are not adequately explained in terms of medial axes, or axes defined by the global object outline. Rather, we argue that axes are defined to allow perspicuous representation of the internal arrangement of object parts. Meeting abstract presented at VSS 2018

Quantitative analysis of in-vivo thumb carpometacarpal joint kinematics using four-dimensional computed tomography.

The purpose of this study was to define the normal thumb carpometacarpal joint kinematics in-vivo during opposition and abduction using four-dimensional computed-tomography in four volunteers. Movement of the metacarpal relative to the trapezium was quantified using both Euler and helical axis representations. Articular surface contact patterns were also analysed. The overall axis of rotation for the movement of opposition and abduction passes through the trapezium and the base of the proximal phalanx, respectively. An abrupt change in instantaneous axis of rotation at terminal opposition was found. Ligament modelling shows dorsoradial ligament becomes tauter towards terminal opposition, whereas anterior oblique ligament becomes more slack. These results support the existence of the 'screw-home' pivot at terminal opposition and the importance of the dorsoradial ligament for stability in this position. The normal reference set in this study can help establish a diagnostic tool for subtle carpometacarpal instability, or for evaluating efficacy of surgery.

The Weighting of Cues to Upright Following Stroke With and Without a History of Pushing.

Perceived upright depends on three main factors: vision, graviception, and the internal representation of the long axis of the body. We assessed the relative contributions of these factors in individuals with sub-acute and chronic stroke and controls using a novel tool; the Oriented Character Recognition Test (OCHART). We also considered whether individuals who displayed active pushing or had a history of pushing behaviours had different weightings than those with no signs of pushing. Three participants experienced a stroke 6 months prior: eight with a history of pushing. In total, 12 participants served as healthy aged-matched controls. Visual and graviceptive cues were dissociated by orienting the visual background left, right, or upright relative to the body, or by orienting the body left, right, or upright relative to gravity. A three-vector model was used to quantify the weightings of vision, graviception, and the body to the perceptual upright. The control group showed weightings of 13% vision, 25% graviception, and 62% body. Some individuals with stroke showed a similar pattern; others, particularly those with recent stroke, showed different patterns, for example, being unaffected by one of the three factors. The participant with active pushing behaviour displayed an ipsilesional perceptual bias (>30°) and was not affected by visual cues to upright. The results of OCHART may be used to quantify the weightings of multisensory inputs in individuals post-stroke and may help characterize perceptual sources of pushing behaviours.

Magneto-Mineralogical Characterization and Manifestations of Magnetic Fabrics from the Gneissic Rocks and Associated Intrusive Bodies in and around Bankura and Purulia Districts, West Bengal, India

The present study aims to unravel the mineralogical, chemical and anisotropy of magnetic susceptibility (AMS) from gneissic rocks and associated pegmatitic bodies from Bankura–Purulia region, West Bengal (India). Petrographic studies were done to detect the textural relationship of minerals that contribute susceptibility with that of the silicates. The study of polished thin-sections under reflected light microscope showed the presence of titano-magnetite and magnetite as dominant magnetic minerals. More than one generation of magnetic minerals were found which are linked to different conditions of temperature and tectonics that prevailed during their oxidation. AMS studies depicted the overall nature of magnetic fabrics (and other related parameters like mean susceptibility, magnetic foliation, magnetic lineation, corrected degree of anisotropy, shape parameter) in the region. The susceptibility ellipsoids were dominantly oblate in the region as evident from the P j –T j plots. The absence of linear relationship between mean susceptibility and degrees of anisotropy proves that the fabrics are independent of bulk ferromagnetic susceptibility and controlled by deformational features. The equal area plots of the principal susceptibility axes and representation of maximum susceptibility axes in the rose diagram revealed parity between the field and magnetic fabrics thus pointing to a tectonic control of fabrics. Moreover, the pegmatitic bodies based on AMS parameters are found to have emplace syn-tectonic to basement deformation which impinged a linear feature (both in mesoscopic fabric and magnetic fabric) to the otherwise undeformed intrusive bodies.

ROTATIONAL MISMATCH OF SELF-ALIGN TIBIAL COMPONENT IN POSTERIOR-STABILIZED (PS) TOTAL KNEE ARTHROPLASTY

Background: Rotational alignment of femoral and tibial prosthesis is one of the important factors for outcomes of total knee arthroplasty (TKA). Rotational malalignment may lead to patellar maltracking, anterior knee pain, femoro-tibial flexion instability and premature wear of the polyethylene inlay. Several studies have demonstrated higher revision rates and less favorable clinical results among patients with rotational malalignment. The transepicondylar axis is widely accepted as the best representation of the functional flexion-extension axis of the knee. On the other hand, no comparable agreement exists for tibial rotational alignment Objectives: The aim of this study was to determine the accurate rotational alignment of components by posterior cruciate lignment substituting TKA using the center-post self-align technique. Method: From January 2007 to May 2009, 54 patients (60 knees) underwent the cemented, posterior ligament substituting TKA using the center-post self-align technique of the tibial component and performed computer tomography postoperatively. The rotational angle between the femoral and tibial components and the rotational variance from the transepicondylar axis were measured. Results: The rotational alignment of femoral components were 90% in the neutral group: 48.3% external rotate (mean 1.15 , range 0.1 – 4.9), 48.3% internal rotate (mean 1.53 , range 0.2 -3.8) and 3.4% were in neutral alignment. The rotation alignment of tibial components were 71.7% in the neutral group: 41.2% external rotate (mean 2.03 , range 0.2 -6.7), 56.7% internal rotate (mean 2.59 , range 0.3 -6.7) and 1.67% had neutral alignment. We found no rotational mismatch between femoral and tibial components in this study. All 60 knees had good patellar tracking by no thumb test technique without lateral released procedure. Conclusion: Femoral component rotations were mostly in the safe zone. Using the center-post self-align technique in posterior cruciate ligament substiting TKA, tibial component rotation was much more varied than the femur. However, all tibial component rotations were in between medial most and medial 1/3 of the tibial tuberble

Pisa syndrome in Parkinson's disease caused by biased spatial referentials? No

Introduction It has been recently hypothesized that Pisa syndrome (PS), the most dramatic form of lateral trunk tilt occurring in persons with PD, might be caused by a bias in one of the key spatial referential. Despite many recent papers, this issue remains to be solved. This study is the first to comprehensively investigate the representation of the vertical (2 modalities: visual [VV] and postural [PV]), together with the representation of the long body axis (LBA) in a group of PD patients with PS. Methods The study consisted in a double-blind controlled trial manipulating conditions of deep brain stimulation (DBS) in 18 PD participants (63.4 [5] years, 11 females, disease duration 18.5 [4.7] years) treated with bilateral DBS of the subthalamic nuclei (STN) (11.8 [2.9] years postdiagnosis) and presenting with a PS. VV, PV and LBA were tested off medication under four condition of STN stimulation (bilateral on, bilateral off, unilateral on/off, unilateral off/on). Motor state (UPDRS), scoliosis and lateral trunk tilt were also precisely assessed. Twenty healthy age- and gender-matched participants were also included (61.4 [6.4] years, 12 females, P = 0.36 and P = 0.94). Results The median lateral trunk tilt was 7.6°(5.5) when patients were instructed to stand as upright as possible. Scoliosis prevalence was high (71%) with a mean Cobb angle 18.8°(7.6). No link was found between the side of the PS and the asymmetry of denervation at the onset of the disease (10/18 tilted to the side of the most denervated striatum) or asymmetry of current symptoms (11/18 tilted toward the most affected hemibody). Spatial referential were more frequently biased in PS than in controls (P < 0.05): VV 7/18; PV 4/18; LBA. Transmodal vertical biases (VV + PV) were rare: 2/18. A possible causal relationship between any of these biases and PS was found in only 3 participants. No statistical rule was found between any of biased referential (side or magnitude) and the trunk tilt (side or magnitude). No spatial referential was modulated by DBS. Discussion–conclusion If VV, PV and LBA are frequently biased in PD persons with PS, this is not the origin of their lateral trunk tilt.