Alignment Of Objects Research Articles

INTERACTION CROSS SECTIONS AND SURVIVAL RATES FOR PROPOSED SOLAR SYSTEM MEMBER PLANET NINE

ABSTRACT Motivated by the report of a possible new planetary member of the solar system, this work calculates cross sections for interactions between passing stars and this proposed Planet Nine. Evidence for the new planet is provided by the orbital alignment of Kuiper belt objects, and other solar system properties, which suggest a Neptune-mass object on an eccentric orbit with a semimajor axis a 9 ≈ 400–1500 au. With such a wide orbit, Planet Nine has a large interaction cross section and is susceptible to disruption by passing stars. Using a large ensemble of numerical simulations (several million) and Monte Carlo sampling, we calculate the cross sections for different classes of orbit-altering events: (A) scattering the planet into its proposed orbit from a smaller orbit, (B) ejecting it from the solar system from its current orbit, (C) capturing the planet from another system, and (D) capturing a free-floating planet. Results are presented for a range of orbital elements with planetary mass m 9 = 10 M ⊕. Removing Planet Nine from the solar system is the most likely outcome. Specifically, we obtain ejection cross sections σ int ∼ 5 × 106 au2 (5 × 104 au2) for environments corresponding to the birth cluster (field). With these cross sections, Planet Nine is likely to be ejected if the Sun resides within its birth cluster longer than Δt ≳ 100 Myr. The probability of ejecting Planet Nine due to passing field stars is ≲3% over the age of the Sun. Probabilities for producing the inferred Planet Nine orbit are low (≲5%).

Correction of GPR wave velocity at different oblique angles between traverses and alignment of line objects in a common offset antenna setting

Estimation of ground penetrating radar's wave velocity in materials is a critical step to accurately estimate depth of embedded line objects in concrete structures, and wetness of material. Errors of velocity are defined as the deviations between the velocities obtained in various oblique angles and those obtained in the traverse normal to the object orientation in a common offset antenna setting. In this paper, we quantified and corrected the errors of such estimation. GPR traverses were designed to travel in various oblique angles θ (90°, 75°, 60° and 45°) relative to the steel bars at 5 cover depths (55mm, 85mm, 115mm, 145mm and 175mm). GPR wave velocity at any position within the lateral detection range of steel bars was measured with simple trigonometry in a semi-automated in-house program. It was found that reduction of oblique angles (i.e. θ<90°) causes flatter hyperbolic reflections and the associated errors of velocity can be as much as 30% in the case of an oblique angle 45° before correction. Such errors were corrected after re-scaling the horizontal travel distance with a multiplication factor of sinθ.

Hydrodynamic interactions between two forced objects of arbitrary shape. I. Effect on alignment

We study the properties and symmetries governing the hydrodynamic interaction between two identical, arbitrarily shaped objects, driven through a viscous fluid. We treat analytically the leading (dipolar) terms of the pair-mobility matrix, affecting the instantaneous relative linear and angular velocities of the two objects at large separation. We prove that the instantaneous hydrodynamic interaction linearly degrades the alignment of asymmetric objects by an external time-dependent drive [B. Moths and T. A. Witten, “Full alignment of colloidal objects by programed forcing,” Phys. Rev. Lett. 110, 028301 (2013)]. The time-dependent effects of hydrodynamic interactions are explicitly demonstrated through numerically calculated trajectories of model alignable objects composed of four stokeslets. In addition to the orientational effect, we find that the two objects usually repel each other. In this case, the mutual degradation weakens as the two objects move away from each other, and full alignment is restored at long times.

Mollifying Atmospheric Instability in VideoSurveillance System Using DT-CWT

Atmospheric instability is a challenging problem in video surveillance. This paper describes a new method for mollifying the effects of atmospheric distortion on observed images, particularly in distorted video turbulence which degrades a region of interest (ROI) .Due to this valuable information from video can be lost, and distorted video is of no use. So to extract important information or data from distorted video use CLEAR algorithm which retrieve information from distorted video. This paper describes a new method for mollifying the effects of atmospheric instability on observed images, particularly airborne turbulence which degrades a region of interest (ROI).In order to provide accurate detail or data from objects behind the distorting layer, a simple and efficient frame selection method is proposed to get informative ROIs from only good-quality frames. We solve the space-variant instability called distortion problem using region-based fusion based on the Dual Tree Complex Wavelet Transform (DT-CWT). We also propose an object alignment method for pre-processing the ROI since this can exhibit significant offsets and distortions between frames. Simple haze removal is used as the final step. To remove the haze from distorted video we use the CLEAR algorithm to extract important information from video. The CLEAR algorithm has series of step to clear video and lastly get restored image. For last step i.e., haze removal dark channel prior method is used. The proposed method performs very well with atmospherically instable or distorted video and outperforms other existing methods

Augmented reality visualization: A review of civil infrastructure system applications

In Civil Infrastructure System (CIS) applications, the requirement of blending synthetic and physical objects distinguishes Augmented Reality (AR) from other visualization technologies in three aspects: (1) it reinforces the connections between people and objects, and promotes engineers’ appreciation about their working context; (2) it allows engineers to perform field tasks with the awareness of both the physical and synthetic environment; and (3) it offsets the significant cost of 3D Model Engineering by including the real world background. This paper reviews critical problems in AR and investigates technical approaches to address the fundamental challenges that prevent the technology from being usefully deployed in CIS applications, such as the alignment of virtual objects with the real environment continuously across time and space; blending of virtual entities with their real background faithfully to create a sustained illusion of co-existence; and the integration of these methods to a scalable and extensible computing AR framework that is openly accessible to the teaching and research community. The research findings have been evaluated in several challenging CIS applications where the potential of having a significant economic and social impact is high. Examples of validation test beds implemented include an AR visual excavator-utility collision avoidance system that enables workers to “see” buried utilities hidden under the ground surface, thus helping prevent accidental utility strikes; an AR post-disaster reconnaissance framework that enables building inspectors to rapidly evaluate and quantify structural damage sustained by buildings in seismic events such as earthquakes or blasts; and a tabletop collaborative AR visualization framework that allows multiple users to observe and interact with visual simulations of engineering processes.

Variable coding and object alignment in Spanish: A corpus-based approach

AbstractThis article discusses three variable coding properties of Spanish objects: flagging (

Fine-tuning regression forests votes for object alignment in the wild.

In this paper, we propose a object alignment method that detects the landmarks of an object in 2D images. In the regression forests (RFs) framework, observations (patches) that are extracted at several image locations cast votes for the localization of several landmarks. We propose to refine the votes before accumulating them into the Hough space, by sieving and/or aggregating. In order to filter out false positive votes, we pass them through several sieves, each associated with a discrete or continuous latent variable. The sieves filter out votes that are not consistent with the latent variable in question, something that implicitly enforces global constraints. In order to aggregate the votes when necessary, we adjusts on-the-fly a proximity threshold by applying a classifier on middle-level features extracted from voting maps for the object landmark in question. Moreover, our method is able to predict the unreliability of an individual object landmark. This information can be useful for subsequent object analysis like object recognition. Our contributions are validated for two object alignment tasks, face alignment and car alignment, on data sets with challenging images collected in the wild, i.e., the Labeled Face in the Wild, the Annotated Facial Landmarks in the Wild, and the street scene car data set. We show that with the proposed approach, and without explicitly introducing shape models, we obtain performance superior or close to the state of the art for both tasks.

Interactive partial 3D shape matching with geometric distance optimization

In this paper, we propose an efficient method for partial 3D shape matching based on minimizing the geometric distance between the source and the target geometry. Unlike existing methods, our method does not use a feature-based distance in order to obtain a matching score. Instead, we use a fast, GPU-based method to approximate the true geometric distance between the source and the target by rendering the source object into a distance field which was built around the target. This function behaves smoothly in the space of transformations and allows for an efficient gradient-based local optimization. In order to overcome local minima, we use single point correspondences between surface points on the source and the target respectively employing simple, yet efficient local features based on the distribution of normal vectors around a reference point. The best correspondences define starting positions for a local optimization. The high efficiency of the distance computation allows for robust determination of the global minima in less than a second, which makes our method usable in interactive applications. Our method works for any kind of input data since it only requires point data with normal information at each point. We also demonstrate the capability of our algorithm to perform global alignment of similar 3D objects.

Exploiting Regular Patterns to Group Persistent Scatterers in Urban Areas

Urban areas are often characterized by geometrically simple and repetitive patterns, in particular, in cases where settlements have been built-up from scratch in a well-planned manner, e.g., according to architectonic, economic, or sociopolitic constraints. This leads to preferred rectangular and regular alignment of objects like windows or balconies at facades for the majority of buildings in modern cities. In this paper, we show how this regularity can be exploited for the challenging task of synthetic aperture radar (SAR) scene description and demonstrate the applicability in case studies. We present a virtually parameter-free method to segment a persistent scatterer point cloud and fit optimal lattices to describe separate facades. Formulating the PS as nodes in a graph allows us to use spectral graph theory to distinguish lattices even when they are overlapping or disturbed due to layover. As a result, we obtain an object-based representation of the SAR data, which allows for many new applications in the field of building monitoring and change detection in urban areas.

Relative accuracy of spin-image-based registration of partial capitate bones in 4DCT of the wrist

In image-based biomechanical analyses, registration transformations are the data of interest. In dynamic four-dimensional computed tomography (4DCT) imaging, the capitate is often partially imaged. While alignment of incomplete objects poses a significant registration challenge, the established spin-image surface-matching algorithm can be utilised to align two surfaces representing disparate but overlapping portions of an object. For this reason, the spin-image algorithm was chosen for the registration of partial bone geometry in 4DCT of the wrist. Registrations were performed on 11 4DCT datasets using complete and partial capitate meshes generated by cropping complete meshes. Relative accuracy was assessed as the difference between partial- and complete-geometry registrations. Accurate registration of partial capitate geometry was achieved with 55% of the proximal capitate geometry on average, and in some cases as little as 35%. Requisite geometry depends on feature salience and imaging resolution; however, the spin-image algorithm should be considered a valuable tool for biomechanists and image analysts.

Multi-classification of cell deformation based on object alignment and run length statistic.

Cellular morphology is widely applied in digital pathology and is essential for improving our understanding of the basic physiological processes of organisms. One of the main issues of application is to develop efficient methods for cell deformation measurement. We propose an innovative indirect approach to analyze dynamic cell morphology in image sequences. The proposed approach considers both the cellular shape change and cytoplasm variation, and takes each frame in the image sequence into account. The cell deformation is measured by the minimum energy function of object alignment, which is invariant to object pose. Then an indirect analysis strategy is employed to overcome the limitation of gradual deformation by run length statistic. We demonstrate the power of the proposed approach with one application: multi-classification of cell deformation. Experimental results show that the proposed method is sensitive to the morphology variation and performs better than standard shape representation methods.

OBJECTS IMAGES ALIGNMENT WITH THE USE OF GENETIC AND GRADIENT ALGORITHMS

The given paper presents a hybrid method which is a combination of genetic and gradient algorithms used for the comparison of digital images of an object. Aligning the images, their basic transformations are taken into account, namely shift and scale in a width and height, angle, changes in intensity and contrast. The software for image alignment of objects has been created using Delphi environment. The program utilizes modified genetic algorithms where the chromosomes are the vectors of real numbers. The methods of roulette, rank and tournament selection are used for chromosome selection. After the use of the genetic algorithm the object images were compared by the method of coordinate descent that provides an accuracy improvement of image alignment. The efficiency of different methods of chromosome selection in the genetic algorithm for images alignment is researched. The size of chromosome population as well as other parameters of genetic algorithm have been optimized.

Ordering

Sketch maps are externalizations of cognitive maps which are typically distorted, schematized, incomplete, and generalized. Processing spatial information from sketch maps automatically requires reliable formalizations which are not subject to schematization, distortion or other cognitive effects in sketch maps. Based on previous empirical work, the authors identified different sketch aspects such as ordering, topology and orientation to align and integrate spatial information from sketch maps with metric maps qualitatively. This research addresses the question how these qualitative sketch aspects can be formalized for a computational approach for sketch map alignment. In this study, the authors focus on the ordering aspect: ordering of landmarks and street segments along routes and around junctions. The authors first investigate different qualitative representations and propose suitable representations to formalize these aspects. The proposed representations capture qualitative relations between spatial objects in the form of qualitative constraint networks. The authors then evaluate the proposed representations by testing the accuracy of qualitative constraints between sketched objects and their corresponding objects in a metric map. The results of the evaluation show that the proposed representations are suitable for the alignment of spatial objects from sketch maps with metric maps.

Dynamics of finite-symmetry and general-shaped objects under shear and shear alignment of uniaxial objects at finite temperatures

We prove that, for an object with a finitefold rotational symmetry (except for a twofold one) around an axis and mirror symmetries (such as a square rod or pentagonal slab, etc.), dynamics of the symmetry axis in low Reynolds number shear flow exactly follows the same form as that of a uniaxial object (e.g., a circular rod or symmetric ellipsoid) as the so-called Jeffery orbits. We use the formulation in which the dynamics of the rigid body follows first-order ordinary differential equations in time [Phys. Rev. E 84, 056309 (2011)]. Interaction between the object and the shear flow enters through a set of scalar coefficients, and the flow field does not need to be solved dynamically. Results of numerical simulations for general-shaped objects also are discussed. In the second part, Brownian dynamics of a uniaxial object is studied numerically. With D as the rotational diffusion constant, α as a parameter characterizing the aspect ratio, and γ as the shear rate, the object starts to align with the flow when the value of D/(γα) decreases near 1. At large α (the long object limit), the results suggest much lower flow alignment when D/(γα)>1.

Orientation Control for Indoor Virtual Landmarks based on Hybrid-based Markerless Augmented Reality

Augmented Reality opens the gate of connection between real and virtual dimension. AR can be used to display any information that by default are not perceived by regular human senses. As such, it is very beneficial to enrich the connection between human and machines. In this paper, an indoor Augmented Reality system is presented in order to display virtual artifacts or ancient heritages in the real, unprepared environment, with the help of camera as the image capturing device. A hybrid sensor-vision markerless tracking algorithm is used as the trackers for camera movement. Vision tracking provides the mapping for unknown environment, and works collaboratively with sensor tracking, so that system can get information where the camera is looking at with respect to the targeted scene. Rendering is then done according to this information. Result shows that the system can display any 3D model in the wide room. The model stays intact when the user moves camera to a different position. The system is also robust to the change of illumination, due to sensor tracking algorithm that does not depend on image features. However, alignment of these virtual objects may fail when rapid, sudden movement occurs in the camera. This study can open more opportunities for AR to be used as a medium of conveying study.

Investigations on User Preferences of the Alignment of Process Activities, Objects, and Roles (Extended Abstract)

Investigations on User Preferences of the Alignment of Process Activities, Objects, and Roles (Extended Abstract)

What limits tool use in nonhuman primates? Insights from tufted capuchin monkeys (Sapajus spp.) and chimpanzees (Pan troglodytes) aligning three-dimensional objects to a surface

Perceptuomotor functions that support using hand tools can be examined in other manipulation tasks, such as alignment of objects to surfaces. We examined tufted capuchin monkeys' and chimpanzees' performance at aligning objects to surfaces while managing one or two spatial relations to do so. We presented six subjects of each species with a single stick to place into a groove, two sticks of equal length to place into two grooves, or two sticks joined as a T to place into a T-shaped groove. Tufted capuchins and chimpanzees performed equivalently on these tasks, aligning the straight stick to within 22.5° of parallel to the groove in approximately half of their attempts to place it, and taking more attempts to place the T stick than two straight sticks. The findings provide strong evidence that tufted capuchins and chimpanzees do not reliably align even one prominent axial feature of an object to a surface, and that managing two concurrent allocentric spatial relations in an alignment problem is significantly more challenging to them than managing two sequential relations. In contrast, humans from 2years of age display very different perceptuomotor abilities in a similar task: they align sticks to a groove reliably on each attempt, and they readily manage two allocentric spatial relations concurrently. Limitations in aligning objects and in managing two or more relations at a time significantly constrain how nonhuman primates can use hand tools.

Fourier Lucas-Kanade Algorithm

In this paper, we propose a framework for both gradient descent image and object alignment in the Fourier domain. Our method centers upon the classical Lucas & Kanade (LK) algorithm where we represent the source and template/model in the complex 2D Fourier domain rather than in the spatial 2D domain. We refer to our approach as the Fourier LK (FLK) algorithm. The FLK formulation is advantageous when one preprocesses the source image and template/model with a bank of filters (e.g., oriented edges, Gabor, etc.) as 1) it can handle substantial illumination variations, 2) the inefficient preprocessing filter bank step can be subsumed within the FLK algorithm as a sparse diagonal weighting matrix, 3) unlike traditional LK, the computational cost is invariant to the number of filters and as a result is far more efficient, and 4) this approach can be extended to the Inverse Compositional (IC) form of the LK algorithm where nearly all steps (including Fourier transform and filter bank preprocessing) can be precomputed, leading to an extremely efficient and robust approach to gradient descent image matching. Further, these computational savings translate to nonrigid object alignment tasks that are considered extensions of the LK algorithm, such as those found in Active Appearance Models (AAMs).

Full Alignment of Colloidal Objects by Programed Forcing

By analysis and simulation, we demonstrate two methods for achieving complete orientational alignment of a set of identical asymmetric colloidal objects dispersed randomly in a fluid. Sedimentation or electrophoresis in a constant field can lead to partial alignment, in which the objects rotate about a common body axis, but the phases of rotation for these objects are random. We show that this phase disorder can be removed by two forms of programed forcing. First, simply alternating the forcing between two directions reduces the statistical entropy of the orientation arbitrarily. Second, the addition of a small rotating component to the applied field in analogy to magnetic resonance can lead to phase locking of the objects' orientation. We identify conditions for alignment of a broad class of generic objects and discuss practical limitations.

An Integrated Region-, Boundary-, Shape-Based Active Contour for Multiple Object Overlap Resolution in Histological Imagery

Active contours and active shape models (ASM) have been widely employed in image segmentation. A major limitation of active contours, however, is in their 1) inability to resolve boundaries of intersecting objects and to 2) handle occlusion. Multiple overlapping objects are typically segmented out as a single object. On the other hand, ASMs are limited by point correspondence issues since object landmarks need to be identified across multiple objects for initial object alignment. ASMs are also are constrained in that they can usually only segment a single object in an image. In this paper, we present a novel synergistic boundary and region-based active contour model that incorporates shape priors in a level set formulation with automated initialization based on watershed. We demonstrate an application of these synergistic active contour models using multiple level sets to segment nuclear and glandular structures on digitized histopathology images of breast and prostate biopsy specimens. Unlike previous related approaches, our model is able to resolve object overlap and separate occluded boundaries of multiple objects simultaneously. The energy functional of the active contour is comprised of three terms. The first term is the prior shape term, modeled on the object of interest, thereby constraining the deformation achievable by the active contour. The second term, a boundary-based term detects object boundaries from image gradients. The third term drives the shape prior and the contour towards the object boundary based on region statistics. The results of qualitative and quantitative evaluation on 100 prostate and 14 breast cancer histology images for the task of detecting and segmenting nuclei and lymphocytes reveals that the model easily outperforms two state of the art segmentation schemes (geodesic active contour and Rousson shape-based model) and on average is able to resolve up to 91% of overlapping/occluded structures in the images.