Representation Of Three-dimensional Objects Research Articles

Three-dimensional chiral objects and their star graph representations

Planar chirality properties can be analysed using n-polyominoes and graphs. In this paper we study graph representations of three-dimensional chiral objects and discuss the generalization of planar case. We show that graph representations of three-dimensional chiral objects can be star graphs.

CBCT in Orthodontics: The Wave of Future

Cone beam computed tomography (CBCT) has probably been one of the most revolutionary innovations in the field of dentistry in the past decade and it provides a novel platform for orthodontic diagnosis and treatment planning. Current imaging techniques are essentially two-dimensional (2D) representations of threedimensional (3D) objects and suffer from several limitations. Hence, fulfillment of ideal imaging goals has been limited. Twodimensional radiographs are insufficient, especially in complex cases like impacted teeth, supernumerary teeth and orthognathic surgeries. CBCT images provide far more detailed information than conventional 2D radiographs and are user friendly. Soft tissues, skull, airway and the dentition can be observed and measured on CBCT images in a 1:1 ratio. CBCT provides an excellent tool for accurate diagnosis, more predictable treatment planning, more efficient patient management and education, improved treatment outcome and patient satisfaction. This article focuses on various applications of cone beam CT technology in orthodontics.

Representation of three‐dimensional objects by the rat perirhinal cortex

The perirhinal cortex (PRC) is known to play an important role in object recognition. Little is known, however, regarding the activity of PRC neurons during the presentation of stimuli that are commonly used for recognition memory tasks in rodents, that is, three-dimensional objects. Rats in the present study were exposed to three-dimensional objects while they traversed a circular track for food reward. Under some behavioral conditions, the track contained novel objects, familiar objects, or no objects. Approximately 38% of PRC neurons demonstrated "object fields" (a selective increase in firing at the location of one or more objects). Although the rats spent more time exploring the objects when they were novel compared to familiar, indicating successful recognition memory, the proportion of object fields and the firing rates of PRC neurons were not affected by the rats' previous experience with the objects. Together, these data indicate that the activity of PRC cells is powerfully affected by the presence of objects while animals navigate through an environment; but under these conditions, the firing patterns are not altered by the relative novelty of objects during successful object recognition.

Picture recognition of food by macaques (Macaca silenus)

Pictorial representations of three-dimensional objects are often used to investigate animal cognitive abilities; however, investigators rarely evaluate whether the animals conceptualize the two-dimensional image as the object it is intended to represent. We tested for picture recognition in lion-tailed macaques by presenting five monkeys with digitized images of familiar foods on a touch screen. Monkeys viewed images of two different foods and learned that they would receive a piece of the one they touched first. After demonstrating that they would reliably select images of their preferred foods on one set of foods, animals were transferred to images of a second set of familiar foods. We assumed that if the monkeys recognized the images, they would spontaneously select images of their preferred foods on the second set of foods. Three monkeys selected images of their preferred foods significantly more often than chance on their first transfer session. In an additional test of the monkeys' picture recognition abilities, animals were presented with pairs of food images containing a medium-preference food paired with either a high-preference food or a low-preference food. The same three monkeys selected the medium-preference foods significantly more often when they were paired with low-preference foods and significantly less often when those same foods were paired with high-preference foods. Our novel design provided convincing evidence that macaques recognized the content of two-dimensional images on a touch screen. Results also suggested that the animals understood the connection between the two-dimensional images and the three-dimensional objects they represented.

Integration of disparity and velocity information for haptic and perceptual judgments of object depth

Do reach-to-grasp (prehension) movements require a metric representation of three-dimensional (3D) layouts and objects? We propose a model relying only on direct sensory information to account for the planning and execution of prehension movements in the absence of haptic feedback and when the hand is not visible. In the present investigation, we isolate relative motion and binocular disparity information from other depth cues and we study their efficacy for reach-to-grasp movements and visual judgments. We show that (i) the amplitude of the grasp increases when relative motion is added to binocular disparity information, even if depth from disparity information is already veridical, and (ii) similar distortions of derived depth are found for haptic tasks and perceptual judgments. With a quantitative test, we demonstrate that our results are consistent with the Intrinsic Constraint model and do not require 3D metric inferences (Domini, Caudek, & Tassinari, 2006). By contrast, the linear cue integration model (Landy, Maloney, Johnston, & Young, 1995) cannot explain the present results, even if the flatness cues are taken into account.

Infants’ representations of three-dimensional occluded objects

Infants’ ability to represent objects has received significant attention from the developmental research community. With the advent of eye-tracking technology, detailed analysis of infants’ looking patterns during object occlusion have revealed much about the nature of infants’ representations. The current study continues this research by analyzing infants’ looking patterns in a novel manner and by comparing infants’ looking at a simple display in which a single three-dimensional (3D) object moves along a continuous trajectory to a more complex display in which two 3D objects undergo trajectories that are interrupted behind an occluder. Six-month-old infants saw an occlusion sequence in which a ball moved along a linear path, disappeared behind a rectangular screen, and then a ball (ball–ball event) or a box (ball–box event) emerged at the other edge. An eye-tracking system recorded infants’ eye-movements during the event sequence. Results from examination of infants’ attention to the occluder indicate that during the occlusion interval infants looked longer to the side of the occluder behind which the moving occluded object was located, shifting gaze from one side of the occluder to the other as the object(s) moved behind the screen. Furthermore, when events included two objects, infants attended to the spatiotemporal coordinates of the objects longer than when a single object was involved. These results provide clear evidence that infants’ visual tracking is different in response to a one-object display than to a two-object display. Furthermore, this finding suggests that infants may require more focused attention to the hidden position of objects in more complex multiple-object displays and provides additional evidence that infants represent the spatial location of moving occluded objects.

Use of a double Fourier series for three-dimensional shape representation

The representation of three-dimensional star-shaped objects by the double Fourier series (DFS) coefficients of their boundary function is considered. An analogue of the convolution theorem for a DFS on a sphere is developed. It is then used to calculate the moments of an object directly from the DFS coefficients, without an intermediate reconstruction step. The complexity of computing the moments from the DFS coefficients is O(N 2 log N), where N is the maximum order of coefficients retained in the expansion, while the complexity of computing the moments from the spherical harmonic representation is O(N 2 log 2 N). It is shown that under sufficient conditions, the moments and surface area corresponding to the truncated DFS converge to the true moments and area of an object. A new kind of DFS—the double Fourier sine series—is proposed which has better convergence properties than the previously used kinds and spherical harmonics in the case of objects with a sharp point above the pole of the spherical domain.

The structure of three-dimensional object representations for regular and irregular shapes: Evidence from whole-part matching and repetition priming

The structure of three-dimensional object representations for regular and irregular shapes: Evidence from whole-part matching and repetition priming

Distinct visual working memory systems for view-dependent and view-invariant representation.

BackgroundHow do people sustain a visual representation of the environment? Currently, many researchers argue that a single visual working memory system sustains non-spatial object information such as colors and shapes. However, previous studies tested visual working memory for two-dimensional objects only. In consequence, the nature of visual working memory for three-dimensional (3D) object representation remains unknown.Methodology/Principal FindingsHere, I show that when sustaining information about 3D objects, visual working memory clearly divides into two separate, specialized memory systems, rather than one system, as was previously thought. One memory system gradually accumulates sensory information, forming an increasingly precise view-dependent representation of the scene over the course of several seconds. A second memory system sustains view-invariant representations of 3D objects. The view-dependent memory system has a storage capacity of 3–4 representations and the view-invariant memory system has a storage capacity of 1–2 representations. These systems can operate independently from one another and do not compete for working memory storage resources.Conclusions/SignificanceThese results provide evidence that visual working memory sustains object information in two separate, specialized memory systems. One memory system sustains view-dependent representations of the scene, akin to the view-specific representations that guide place recognition during navigation in humans, rodents and insects. The second memory system sustains view-invariant representations of 3D objects, akin to the object-based representations that underlie object cognition.

Radar Cross Section Measurements and Simulations of a Model Airplane in the X-band

The objective of this study was to illustrate how difierent methods of obtaining the Radar Cross Section (RCS) of an object may produce difierent results. RCS diagrams of a metallic airplane model (length, 0.64m) were obtained in an anechoic chamber, with a Lab- Volt RCS system, and simulated with a simulation software. The measurements and simulations were carried out at the radar frequency of 9.4GHz. The resulting RCS diagrams show that although there was a good correspondence between the main features in the RCS diagrams, some difierences can still be observed, highlighting the need for difierent techniques to fully represent the RCS of an object. Radar cross section (RCS) diagrams are usually di-cult to interpret due to the fact that they are two-dimensional representations of three-dimensional objects. Moreover, the di-culty in interpret- ing RCS diagrams is dependent upon the geometry of the object and, sometimes, on the techniques used to measure or calculate the RCS. Measurements are also afiected by many external factors, such as instrumental errors, spurious re∞ections and interferences, which can degrade the quality of the experimental data. In this study, we measured the RCS of an airplane model with a conduct- ing surface using two difierent experimental set-ups, and also simulated its RCS using commercial electromagnetic simulation software. The comparison of the data obtained shows that difierences will arise regardless of the care taken while performing an experiment or carrying out simulations and that these difierences should be taken into consideration when interpreting the data. 2. EXPERIMENTAL MEASUREMENTS The experimental data were collected using two difierent experimental setups: One inside an ane- choic chamber and another in a laboratory room using the Lab-Volt Radar Training System. The anechoic chamber, is located in the Instituto de Fomento Industrial (IFI/CTA, Brazil). Figure 1 shows the radar antennas used in the measurements. These X-band horn antennas were manufactured by M2SAT (Brazil); each antenna has a gain of 10dBi, and symmetric radiation patterns with low level of secondary lobes. The radar operated at 9.4GHz, in a quasi-monostatic conflguration and vertical polarization. A HP8360B (HP, USA) synthesized CW generator was use to generate the microwave radiation and the re∞ected signal was analyzed by a HP8593E (HP, USA) spectrum analyzer. It is estimated that the deviation of the RCS measurements was within 0.7dB. The model used in the measurements is also shown in Figure 1; it is a scale model of a Boeing 777 with total length of 0.64m (» 20‚). The body of the model is composed of an epoxy resin and its surface is coated with aluminum (the thickness of the coating is about 10 times larger than the skin depth of the aluminum at this frequency). The distance between the radar antennas and the model was about 6m. Electronic Warfare Laboratory (LGE/CTA, Brazil), consisting of interconnected subsystems that allow detailed studies of RCS in a laboratory environment. Measurements were carried out with inverse synthetic aperture radar, operating also at 9.4GHz at short range, in the presence of noise and clutter. The efiects of noise and clutter were removed using time-gating and subtraction techniques during the measurements. For the measurements, the distance between antenna and model was the same one used for the measurements in the anechoic chamber. Figure 2 shows the arrangement of the radar antenna and the model in the laboratory. The model was placed on a Styrofoam pedestal, invisible to radar waves.

Simulating the design of special cutting tools

Currently, in simulating the design of special cutting tools, different models (graphs, analytical dependences, functional models) and methods (three-dimensional representation of objects, search methods, etc.) are used. The goal of simulation is to improve the cutting tool at the design stage and to obtain tool characteristics guaranteeing the manufacture of parts of specified quality in different combinations of cutting conditions, machine tools, software, and hardware. A unified design and production system is organized within the framework of a general quality-control system, covering the whole tool lifetime, from obtaining the order for its design to its withdrawal from service. Currently, there are no integrated methods of cuttingtool design within a unified CAD/CAE/CAM/PLM environment based on common algorithms and rules. The method proposed for organizing this environment is based on functional simulation of the design of special cutting tools. The design stage takes the form of processes divided into functions reflecting the current state of these processes and functions permitting their redesign. Automation of the design of manufacturing technologies for cutting tools may be analyzed on the basis of the general principles of computer-assisted systems used in the design of manufacturing processes for general-purpose machine parts [1, 2]. In this approach, in particular, the cutting tool is not considered as an object of design and production, with properties differing from those of machine parts. The cutting tool may be regarded from two points of view, as shown in [3]: as a certain object for which manufacturing processes must be designed; and as a component with a specified function, for producing parts of specified dimensions. In the latter case, a machining method employing a cutting tool selected by the technologist is determined; the tool may be of different designs. Obviously, these perspectives are fundamentally different: in the first, the cutting tool is considered without taking account of the technological-design goals; in the second, it is regarded as a component of this process, permitting different production sequences. Depending on the selected approach, the design of the computer-assisted design system will take different forms. Aspects of the cutting tool that must be taken into account in its design and manufacture were identified in [3]: the many technologically equivalent design options; and the possibility of formulating approximation problems. This calls for the creation of an integrated CAD system for the cutting tool, covering both its design and the formulation of an appropriate manufacturing technology. On the basis of the components of the CAD system, a functional model of cutting-tool design may be created (Fig. 1). In stage 1 (deriving the design constants), the parameters of the tool (tooth geometry, length of the cutting and calibrating sections, tooth spacing, etc,) that guarantee specified quality of the manufactured part are determined, taking account of the initial data for the machined parts (the type of material, the required surface roughness, the optimal cutting conditions, etc.) and the available resources. In stage 2 (determining the variable structural components), technological pathways (TP) of cutting-tool manufacture, operating technologies (OT), and control programs (CP) for the machining of cutting tools on numerically controlled machine tools are developed, taking account of the design standards (I) and also the constraints on the implementation of the new techno

Geometric algorithms for manufacturing of freeform multi-material objects using reconfigurable tools

In this research, geometric algorithms for representation and fabrication of three-dimensional (3D) freeform multi-material objects using a rapidly reconfigurable moulding process have been presented. The rapidly reconfigurable moulding system consists of many discrete arrays of pins each forming the mould-face of a mould block. A new material representation scheme is proposed for freeform multi-material objects. The geometric algorithms detailed in this paper analyse the given multi-material object and decompose it based on the material regions and manufacturability of the regions using silhouette-edge based method. The processing sequence is then determined to fabricate the decomposed multi-material object using the reconfigurable moulding process. Computer implementation and illustrative examples are also presented.

Efficient three-dimensional object representation and reconstruction using depth and texture maps

This paper introduces an effective representation method for 3-D shape and texture, to be called DOC/TOC (“Depth/texture on cylinder”), and a depth estimation algorithm that is appropriate to representation in an image-based rendering environment using multiview input images. In this framework, we show that this representation is also useful for object reconstruction. While previous reconstruction methods focus on the estimation of 3-D information only, we consider compactness and effectiveness of the information, and reconstruction results as well. DOC/TOC represents 3-D information on a 2-D cylinder surface by projection on that surface. The inner-boundary loss of the projection is complemented by using multiple depth values. This method is also a good starting point for mesh generation for 3-D reconstruction. Experimental results show that the proposed methods successfully represent and reconstruct the shape and texture of 3-D objects without information loss. Results of this research are applicable to other various types of intermediate surface.

Virtual surgery simulation for medical training using multi‐resolution organ models

Real-time simulation of organ deformation is one of the biggest challenges in virtual surgery, due to the conflicting requirements of real-time interactivity and simulation realism. In this paper we propose a method to overcome this challenge by introducing a multi-resolution modelling technique. In our approach a reasonably coarse global model is locally enhanced, using a mesh subdivision and smoothing algorithm. The global model is based on a discretization of the boundary integral representation of three-dimensional deformable objects. Local refinements are provided at the tool-tissue interaction region by a local subdivision technique. As an example, we have developed a deformable human kidney model generated from the Visible Human Dataset, with tissue properties determined from in vivo animal experiments. A mixed reality laparoscopic surgical training system has been developed, using an abdominal mannequin and force feedback devices. The use of precomputation and structural re-analysis techniques results in a very rapid computation procedure. Validation of the simulator is in progress.

Neural-Network-Based Models of 3-D Objects for Virtualized Reality: A Comparative Study

The paper presents a comprehensive analysis and comparison of the representational capabilities of three neural architectures for three-dimensional (3-D) object representation in terms of purpose, computational cost, complexity, conformance and convenience, ease of manipulation, and potential applications in the context of virtualized reality. Starting from a pointcloud that embeds the shape of the object to be modeled, a volumetric representation is obtained using a multilayer feedforward neural network (MLFFNN) or a surface representation using either the self-organizing map (SOM) or the neural gas network. The representation provided by the neural networks (NNs) is simple, compact, and accurate. The models can be easily transformed in size, position, and shape. Some potential applications of the presented architectures in the context of virtualized reality are for the modeling of set operations and object morphing, for the detection of object collision, and for object recognition, object motion estimation, and segmentation.

Studies on depth‐of‐field effects in microscopy supported by numerical simulations

Micrographs are two-dimensional (2D) representations of three-dimensional (3D) objects. When the depth-of-field of a micrograph is comparable with or larger than the characteristic dimension of objects within the micrograph, measured 2D parameters (e.g. particle number density, surface area of particles, fraction of open space) require stereological correction to determine the correct 3D values. Here, we develop a stereological theory using a differential approach to relate the 3D volume fraction and specific surface area to the 2D projected area and perimeter fractions, accounting for the influence of depth-of-field. The stereological theory is appropriate for random isotropic arrangements of non-interpenetrating particles and is valid for convex geometries (e.g. spheres, spheroids, cylinders). These geometrical assumptions allow the stereological formulae to be expressed as a set of algebraic equations incorporating a single parameter to describe particle shape that is tightly bounded between 1.5pi and 2pi. The stereological theory may also be applied to arrangements of interpenetrating convex particles, and for this case, the resulting stereological formulae become identical to the formulae previously presented by Miles. To test the accuracy of the stereological theory, random computational arrangements of non-interpenetrating and interpenetrating spheres or cylinders are analysed, and the projected area and perimeter fractions are numerically determined as a function of depth-of-field. The computational results show very good agreement with the theoretical predictions over a broad range of depth-of-field, volume fraction and particle geometry for both non-interpenetrating and interpenetrating particles, demonstrating the overall accuracy of the stereological theory. Applications of the stereological theory towards analysis of biological tissues and extracellular matrix are discussed.

The Structure of Three-Dimensional Object Representations in Human Vision: Evidence From Whole-Part Matching.

This article examines how the human visual system represents the shapes of 3-dimensional (3D) objects. One long-standing hypothesis is that object shapes are represented in terms of volumetric component parts and their spatial configuration. This hypothesis is examined in 3 experiments using a whole-part matching paradigm in which participants match object parts to whole novel 3D object shapes. Experiments 1 and 2, consistent with volumetric image segmentation, show that whole-part matching is faster for volumetric component parts than for either open or closed nonvolumetric regions of edge contour. However, the results of Experiment 3 show that an equivalent advantage is found for bounded regions of edge contour that correspond to object surfaces. The results are interpreted in terms of a surface-based model of 3D shape representation, which proposes edge-bounded 2-dimensional polygons as basic primitives of surface shape.

Construction of a Three-Sided Immersive Telecollaboration System

In this article the setup and working principle of a new telecollaboration system “blue-c” is described. This system is an attempt to meet the rising expectations from industry of an IT-supported telecollaboration system. One basic requirement is that a three-dimensional representation of objects be possible together with threedimensional representations of the remote users. Since gesture and mimicry represent an important information channel during a discussion, a realistic 3D video representation is used instead of simple animated avatars.A simultaneous projection and image acquisition of the user in a telecollaboration system is necessary to allow simultaneous work of all team members. Thus, in the introduced system, problems had to be overcome such as providing, simultaneously, illumination for the image acquisition by the cameras and darkness for a bright projection to be seen by the user. A new approach was taken to integrate the cameras into the system by placing them behind active projection walls, which can be switched from transparent to opaque electrically. Unlike other systems, the cameras are therefore not visible to the user, who thus behaves more naturally. In addition, since the cameras are placed outside of the projection room, there is more space to move inside the immersive environment.The article describes the technology and functionality of the system, as well as the gathered experiences.

Classification objects, ideal observers & generative models

AbstractA successful vision system must solve the problem of deriving geometrical information about three‐dimensional objects from two‐dimensional photometric input. The human visual system solves this problem with remarkable efficiency, and one challenge in vision research is to understand howneural representations of objects are formed and what visual information is used to form these representations. Ideal observer analysis has demonstrated the advantages of studying vision from the perspective of explicit generative models and a specified visual task, which divides the causes of image variations into the separate categories of signal and noise. Classification image techniques estimate the visual information used in a task from the properties of “noise” images that interact most strongly with the task. Both ideal observer analysis and classification image techniques rely on the assumption of a generative model. We show here how the ability of the classification image approach to understand how an observer uses visual information can be improved by matching the type and dimensionality of the model to that of the neural representation or internal template being studied. Because image variation in real world object tasks can arise from both geometrical shape and photometric (illumination or material) changes, a realistic image generation process should model geometry as well as intensity. A simple example is used to demonstrate what we refer to as a “classification object” approach to studying three‐dimensional object representations.

Classification objects, ideal observers & generative models

A successful vision system must solve the problem of deriving geometrical information about three-dimensional objects from two-dimensional photometric input. The human visual system solves this problem with remarkable efficiency, and one challenge in vision research is to understand how neural representations of objects are formed and what visual information is used to form these representations. Ideal observer analysis has demonstrated the advantages of studying vision from the perspective of explicit generative models and a specified visual task, which divides the causes of image variations into the separate categories of signal and noise. Classification image techniques estimate the visual information used in a task from the properties of “noise” images that interact most strongly with the task. Both ideal observer analysis and classification image techniques rely on the assumption of a generative model. We show here how the ability of the classification image approach to understand how an observer uses visual information can be improved by matching the type and dimensionality of the model to that of the neural representation or internal template being studied. Because image variation in real world object tasks can arise from both geometrical shape and photometric (illumination or material) changes, a realistic image generation process should model geometry as well as intensity. A simple example is used to demonstrate what we refer to as a “classification object” approach to studying three-dimensional object representations.