Multi-resolution Model Research Articles

The Multi-Resolution Modeling of CTCS-3 Visualization Based on Meta-Model

Chinese train control system is abbreviated as CTCS. And there are five levels in CTCS, and CTCS-3 is used for the high speed railway which includes the long rail lines, the different regions, and the rich variety of scenes. It is very important to describe efficiently the relation of the objects for the design and the modeling of the railway visualization. This paper proposes the multi-resolution modeling of CTCS-3 visualization based on meta-model, and introduces the formal description of this meta-model by XML. The formal description examples have certified that this method can provide the enough grammar rules for the reusability of CTCS-3 visualization model.

Multispectral textured image segmentation using a multi-resolution fuzzy Markov random field model on variable scales in the wavelet domain

This article proposes a new multispectral image texture segmentation algorithm using a multi-resolution fuzzy Markov random field model for a variable scale in the wavelet domain. The algorithm considers multi-scalar information in both vertical and lateral directions. The feature field of the scalable wavelet coefficients is modelled, combining with the fuzzy label field describing the spatially constrained correlations between neighbourhood features to achieve a more accurate parameter estimation. The extended scalable label field models the label data from different scales to obtain more homogeneous areas; image segmentation results are finally obtained according to the Bayesian rule from a coarser to a finer scale. Multispectral texture images and remote-sensing images are used to test the effectiveness of the the proposed method. Segmentation results show that the new method simultaneously presents a better performance in achieving the homogeneity of the region and accuracy of detected boundaries compared with existing image segmentation algorithms.

Integration method of TINs and Grids for multi-resolution surface modeling

Highly detailed surface models and their real-time applications are increasingly popular in architecture, construction and other design and engineering fields. However, new and related problems have emerged concerning the efficient management of the resulting large datasets and the seamless integration of heterogeneous data. Moreover, the increasingly common requirements of local high-fidelity modeling combined with large-scale landscapes lead to difficulty in the seamless multi-resolution representation of hybrid triangulated irregular networks (TINs) and Grids. This paper presents a hybrid data structure with high-efficiency and a related organizational method for the seamless integration of multi-resolution models. This approach is characterized by (1) a self-adaptive algorithm for feature-preserving surface partitioning, (2) an efficient hybrid index structure for combined Grid and TIN surfaces, and (3) a view-dependent scheduling strategy with access to Grids of necessary resolution, giving priority to the dynamic loading of TINs. Experiments using typical real design datasets of highway constructions are able to achieve accuracy-preserved and real-time availability of results that prove the validity and efficiency of this approach.

PhotoCloud: Interactive remote exploration of joint 2D and 3D datasets.

PhotoCloud is a real-time client-server system for interactive visualization and exploration of large datasets comprising thousands of calibrated 2D photographs of a scene and a complex 3D description of the scene. The system isn't tailored to any specific data acquisition process; it aims at generality and flexibility. PhotoCloud achieves scalability through a multiresolution dynamic hierarchical representation of the data, which is remotely stored and accessed by the client through an efficient cache system. The system includes a compact image browser and a multiresolution model renderer. PhotoCloud employs iconic visualization of the images in the 3D space and projects images onto the 3D scene on the fly. Users can navigate the 2D and 3D spaces with smooth, integrated, seamless transitions between them. A study with differently skilled users confirms PhotoCloud's effectiveness and communication power. The Web extras at http://www.youtube.com/playlist?list=PLHJB2bhmgB7cmYD0ST9CEDMRv1JlX4xPH are videos demonstrating PhotoCloud, a real-time client-server system for interactive exploration of large datasets comprising 2D photos and 3D models.

Multi‐Resolution Simulation of Biomolecular Systems: A Review of Methodological Issues

Theoretical-computational modeling with an eye to explaining experimental observations in regard to a particular chemical phenomenon or process requires choices concerning essential degrees of freedom and types of interactions and the generation of a Boltzmann ensemble or trajectories of configurations. Depending on the degrees of freedom that are essential to the process of interest, for example, electronic or nuclear versus atomic, molecular or supra-molecular, quantum- or classical-mechanical equations of motion are to be used. In multi-resolution simulation, various levels of resolution, for example, electronic, atomic, supra-atomic or supra-molecular, are combined in one model. This allows an enhancement of the computational efficiency, while maintaining sufficient detail with respect to particular degrees of freedom. The basic challenges and choices with respect to multi-resolution modeling are reviewed and as an illustration the differential catalytic properties of two enzymes with similar folds but different substrates with respect to these substrates are explored using multi-resolution simulation at the electronic, atomic and supra-molecular levels of resolution.

Design, Analysis and Additive Manufacturing of Porous Structures for Biocompatible Micro-Scale Scaffolds

Advancements in the fields of biocompatible materials, manufacturing processes, computational methods and medicine have led to the emergence of a new field: micro-scale scaffolds for bone replacement and regeneration. Yet most such scaffolds produced today are characterized by very basic geometry, and their microstructure differs greatly from that of the actual tissue they are intended to replace. In this paper, we propose a novel approach for generating micro-scale scaffolds based on processing actual micro-CT images and then reconstructing a highly accurate geometrical model. This model is manufactured by means of a state-of-the-art 3D additive manufacturing process from biocompatible materials. At the micro-scale level, these scaffolds are very similar to the original tissue, thus interfacing better with the surrounding tissue and facilitating more efficient rehabilitation for the patient. Moreover, the approach facilitates the design and manufacture of patient-specific scaffolds which can copy patients’ exact structural and mechanical characteristics, taking into account their physical condition and medical history. By means of multi-resolution volumetric modeling methods, scaffold porosity can also be adapted according to specific mechanical requirements. The process of designing and manufacturing micro-scale scaffolds involves five major stages: (a) building a volumetric multi-resolution model from micro-CT images; (b) generation of surface geometric model in STL format; (c) additive manufacturing of the scaffold; (d) scaffold shape verification relative to the geometric design; and (e) verification of mechanical properties through finite element analysis. In this research, all the proposed stages of the approach were tested. The input included micro-CT scans of porous ceramic structure, which is quite similar to commercial porous scaffolds. The results show that the proposed method is feasible for design and manufacture of micro-scale scaffolds.

Multiresolution Visualization Tools to Aid in Conducting Road Safety Audits

Typical road safety audits use site investigations in addition to historical data to make recommendations. Recent approaches have used simulation modeling to derive surrogate measures to analyze the potential for collisions, driving simulators to analyze human behavior, or other visualization tools to analyze geometric design characteristics. None of these tools can capture the dynamics of proposed changes that subsequently alter traffic patterns. Each proposed improvement has an influence on traffic patterns and must be captured at a regional level to determine whether vehicles choose the same path or defer to an alternative one. This study explored new methods to supplement the Road Safety Audit process. The study used visualization tools to assess the performance of each proposed improvement strategy by conducting a more thorough comprehensive safety study with multiresolution modeling methods in situations when suggested countermeasures would almost certainly redistribute traffic to alternative routes. A case study was selected in which an audit team performed a safety audit of a diamond interchange in El Paso, Texas, that experienced a high number of collisions during peak hours. The visualization of the proposed improvement scenarios helped the Texas Department of Transportation understand better how mitigation strategies would influence traffic flow in and around the study area or whether the proposed changes improved safety or merely shifted the problem to alternative locations. The use of visualization tools can help convey proposed improvements to the public.

Multiresolution Modeling of the Dynamic Loading of Metal Matrix Composites

The mechanical behavior of metal matrix composites (MMCs) varies significantly under rapid straining as compared to quasi-static loading and is often dominated by underlying microstructural features (grain structure, porosity, inclusions, and defects). Analysis of the behavior of MMCs under dynamic loading requires theoretical and experimental approaches that integrate the strain rate and microstructural effects. In this article, we introduce a multiresolution modeling capability for studying nonlinear planar wave propagation in heterogeneous materials with an application to MMCs. This framework is based on direct numerical simulation (DNS) and compared to an upscaled microcontinuum model. The DNS explicitly accounts for microstructural features characterizing the materials and is based on a combination of a crystal plasticity formulation for the behavior of the host matrix and the Johnson–Holmquist model for the particulate reinforcements. The nonuniformity of the wave propagating through MMCs is spatially resolved. The results from the mesoscale DNS are used to inform a microcontinuum model that introduces richer kinematics to account for microstructural features without explicitly modeling them and with far fewer total degrees of freedom. A quantitative comparison of the reduced degrees of freedom model against DNS is performed and enables us to draw conclusions on the predictive capability of the microcontinuum model to study the dynamic response of heterogeneous materials.

The utility of remotely-sensed vegetative and terrain covariates at different spatial resolutions in modelling soil and watertable depth (for digital soil mapping)

Digital soil modelling and mapping is reliant on the availability and utility of easily derived and accessible covariates. In this paper, the value of covariates derived from a time-series of remotely-sensed ASTER satellite imagery and digital elevation models were evaluated for modelling two soil attributes — soil depth and watertable depth. Modelling was performed at two resolutions: a fine resolution (15m pixels) that relates to the resolution of the ASTER Visible-NIR bands, and a larger resolution (90m pixels) that relates to the resolution of the thermal bands of the ASTER imagery. Upscaling to a larger pixel size and downscaling to a smaller pixel size were performed to adjust the covariates where necessary. A regression tree approach was used to model soil depth and watertable depth, recorded as a binary ‘deep’ or ‘shallow’ response, using the ASTER imagery-derived covariates and digital terrain attributes (DTAs). Modelling was performed at a single spatial resolution (15 or 90m pixels) using the imagery-derived covariates only, the DTAs only, or a mixture of both. A multi-resolution model was also generated, by using both imagery-derived covariates and DTAs at both resolutions. When mixed with the DTAs, the imagery-derived covariates helped explain the uncertainty (variance) in the soil depth data but not in the watertable depth. The ASTER-derived downscaled evapotranspiration-based covariates were of particular significance in the soil depth modelling. Watertable depth was best explained by models that used DTAs at a smaller pixel size. Information on vegetative growth was neither superior nor complementary to information on terrain for modelling watertable depth. Using a multi-resolution model significantly improved the modelling of soil depth but not of watertable depth. The effect of covariate and modelling resolution on model performance is discussed within the context of the GlobalSoilMap.net project.

Compression of Multi-Resolution Terrain Data Based on Binary Tree

In order to overcome the incontinuity and redundancy of data storage caused by the grids in representing the multi-resolution terrain, an adaptive hierarchical triangulation based on binary tree is used to represent the multi-resolution terrain model. It realizes the representation of the terrain data at different levels of detail and enables data compression by local omission of data values. The structure of binary tree is stored using a bit code of the underlying binary tree, while the height data are stored using an array, and relative pointers which allow a selective tree traversal. This method realizes the continuity and reduces the data volume in data storage of multi-resolution digital elevation model (DEM), and it is possible to work directly on the compressed data. We show that significant compression rates can be obtained already for small threshold values, and in a visualization application, it is possible to extracted and drawn triangulations at interactive rates.

Sparse imaging of cortical electrical current densities via wavelet transforms

While the cerebral cortex in the human brain is of functional importance, functions defined on this structure are difficult to analyze spatially due to its highly convoluted irregular geometry. This study developed a novel L1-norm regularization method using a newly proposed multi-resolution face-based wavelet method to estimate cortical electrical activities in electroencephalography (EEG) and magnetoencephalography (MEG) inverse problems. The proposed wavelets were developed based on multi-resolution models built from irregular cortical surface meshes, which were realized in this study too. The multi-resolution wavelet analysis was used to seek sparse representation of cortical current densities in transformed domains, which was expected due to the compressibility of wavelets, and evaluated using Monte Carlo simulations. The EEG/MEG inverse problems were solved with the use of the novel L1-norm regularization method exploring the sparseness in the wavelet domain. The inverse solutions obtained from the new method using MEG data were evaluated by Monte Carlo simulations too. The present results indicated that cortical current densities could be efficiently compressed using the proposed face-based wavelet method, which exhibited better performance than the vertex-based wavelet method. In both simulations and auditory experimental data analysis, the proposed L1-norm regularization method showed better source detection accuracy and less estimation errors than other two classic methods, i.e. weighted minimum norm (wMNE) and cortical low-resolution electromagnetic tomography (cLORETA). This study suggests that the L1-norm regularization method with the use of face-based wavelets is a promising tool for studying functional activations of the human brain.

Specification of multi-resolution modeling space for multi-resolution system simulation

Multi-resolution modeling (MRM) represents a real system as a set of models of different resolutions, at different abstraction levels, from the viewpoint of simulation objectives. MRM is a significant technology for complex and large-scale simulation. However, previous research is almost application specific and dependent on a specific simulation algorithm. The concepts separate multi-resolution models from the simulation models, thereby making them adaptable to any existing simulation methodology. This paper proposes a specification of multi-resolution modeling space (MRMS) for multi-resolution system simulation. The proposed specification is based on concepts of decoupling MRM and multi-resolution simulation. This MRMS specification supports MRM in two parts: resolution conversion for dynamically changing simulation model structures and resolution matching interfaces between events in different resolutions. A simple example demonstrates advantages of the proposed specification.

A WEB-BASED INTERACTIVE TOOL FOR MULTI-RESOLUTION 3D MODELS OF A MAYA ARCHAEOLOGICAL SITE

Abstract. Continuous technological advances in surveying, computing and digital-content delivery are strongly contributing to a change in the way Cultural Heritage is "perceived": new tools and methodologies for documentation, reconstruction and research are being created to assist not only scholars, but also to reach more potential users (e.g. students and tourists) willing to access more detailed information about art history and archaeology. 3D computer-simulated models, sometimes set in virtual landscapes, offer for example the chance to explore possible hypothetical reconstructions, while on-line GIS resources can help interactive analyses of relationships and change over space and time. While for some research purposes a traditional 2D approach may suffice, this is not the case for more complex analyses concerning spatial and temporal features of architecture, like for example the relationship of architecture and landscape, visibility studies etc. The project aims therefore at creating a tool, called "QueryArch3D" tool, which enables the web-based visualisation and queries of an interactive, multi-resolution 3D model in the framework of Cultural Heritage. More specifically, a complete Maya archaeological site, located in Copan (Honduras), has been chosen as case study to test and demonstrate the platform’s capabilities. Much of the site has been surveyed and modelled at different levels of detail (LoD) and the geometric model has been semantically segmented and integrated with attribute data gathered from several external data sources. The paper describes the characteristics of the research work, along with its implementation issues and the initial results of the developed prototype.

Application of Similarity Theory in Research on Consistency in Multi-Resolution Modeling

This paper analyzed the function consistency, dominating consistency, state consistency and structural consistency of multi-resolution model based on three principles of the similarity theory. Then, a method of quality evaluation of consistency on state level and structural level are presented. The practice proved that this research is helpful to find the factors which influence the consistency and search for accurate measures to improve the consistency on every level.

Multi-resolution Corrective Demonstration for Efficient Task Execution and Refinement

Computationally efficient task execution is very important for autonomous mobile robots endowed with limited on-board computational resources. Most robot control approaches assume a fixed state and action representation, and use a single algorithm to map states to actions. However, not all situations in a given task require equally complex algorithms and equally detailed state and action representations. The main motivation for this work is a desire to reduce the computational footprint of performing a task by allowing the robot to run simpler algorithms whenever possible, and resort to a more complex algorithm only when needed. We contribute the Multi-Resolution Task Execution (MRTE) algorithm that utilizes human feedback to learn a mapping from a given state to an appropriate detail resolution consisting of a state and action representation, and an algorithm providing a mapping from states to actions at that resolution. The robot learns a policy from human demonstration to switch between different detail resolutions as needed while favoring lower detail resolutions to reduce computational cost of task execution. We then present the Model Plus Correction (M+C) algorithm to improve the performance of an algorithm using corrective human feedback without modifying the algorithm itself. Finally, we introduce the Multi-Resolution Model Plus Correction (MRM+C) algorithm as a combination of MRTE and M+C. MRM+C learns how to select an appropriate detail resolution to operate at in a given state from human demonstration. Furthermore, it allows the teacher to provide corrective demonstration at different detail resolutions to improve overall task execution performance. We provide formal definitions of MRTE, M+C, and MRM+C algorithms, and show how they relate to general robot control problem and Learning from Demonstration (LfD) approach. We present experimental results de-monstrating the effectiveness of proposed methods on a goal-directed humanoid obstacle avoidance task.

Learning and Inference for Graphical and Hierarchical Models: A Personal Journey

This talk will provide an overview of a personal perspective on inference and learning for graphical models, one that began with work on multi-resolution models for signals and images but that has evolved into a more general look at inference and learning especially for graphical models for which these tasks are tractable and scalable to large problems.The talk will begin with a brief introduction to Markov models on undirected graphs and message-passing algorithms, often known as Belief Propagation, that exactly solve inference problems for s on a very special set of graphs, namely those without loops or cycles, i.e., trees. We'll then turn to building or learning models on such graphs, including ones that explicitly have hierarchical structure and will comment on some of the differences between the questions that have typically been addressed in very different communities (namely machine learning and system theory). We'll then provide a new method for learning models on trees with hidden nodes.The rest of the talk will deal with a look at what happens if one considers graphs with loops. We first look at what is known as Loopy Belief Propagation and provide, for the Gaussian case, an explicit picture of what it does and when and why it works and when it doesn't based on what we call walk-sum analysis. We then use these ideas to describe another new set of algorithms based on the graph-theoretic concept of a feedback vertex set (i.e., a set of nodes in the graph that, if removed, leave a cycle-free graph). As time allows we'll discuss the learning of several other classes of graphical models, where in each case, the objective is to learn models for which both the learning of these models as well as exact or nearly exact inference using these models is computational feasible.

3D Visualization Algorithm Based on Terrain Partitioning and Dynamic Levels of Details

By improving on the Quad-tree LOD algorithm, this paper proposes a new algorithm based on the terrain partitioning and simplifying the terrain by using grid models of different levels of detail dynamically.This algorithm can be reduced the number of triangular facets in the terrain scene.The experimental results show that this algorithm can generate continuous multi-resolution terrain model and improve the efficiency of real-time rendering.

Texture Image Segmentation Based on MRMRF in Contourlet Domain

This paper presents a new multi-resolution Markov random field model in Contourlet domain for unsupervised texture image segmentation. In order to make full use of the merits of Contourlet transformation, we introduce the taditional MRMRF model into Contourlet domain, in a manner of variable interation between two components in the tradtional MRMRF model. Using this method, the new model can automatically estimate model parameters and produce accurate unsupervised segmentation results. The results obtained on synthetic texture images and remote sensing images demonstrate that a better segmentation is achieved by our model than the traditional MRMRF model.

CityGML – Interoperable semantic 3D city models

CityGML is the international standard of the Open Geospatial Consortium (OGC) for the representation and exchange of 3D city models. It defines the three-dimensional geometry, topology, semantics and appearance of the most relevant topographic objects in urban or regional contexts. These definitions are provided in different, well-defined Levels-of-Detail (multiresolution model). The focus of CityGML is on the semantical aspects of 3D city models, its structures, taxonomies and aggregations, allowing users to employ virtual 3D city models for advanced analysis and visualization tasks in a variety of application domains such as urban planning, indoor/outdoor pedestrian navigation, environmental simulations, cultural heritage, or facility management. This is in contrast to purely geometrical/graphical models such as KML, VRML, or X3D, which do not provide sufficient semantics. CityGML is based on the Geography Markup Language (GML), which provides a standardized geometry model. Due to this model and its well-defined semantics and structures, CityGML facilitates interoperable data exchange in the context of geo web services and spatial data infrastructures. Since its standardization in 2008, CityGML has become used on a worldwide scale: tools from notable companies in the geospatial field provide CityGML interfaces. Many applications and projects use this standard. CityGML is also having a strong impact on science: numerous approaches use CityGML, particularly its semantics, for disaster management, emergency responses, or energy-related applications as well as for visualizations, or they contribute to CityGML, improving its consistency and validity, or use CityGML, particularly its different Levels-of-Detail, as a source or target for generalizations.This paper gives an overview of CityGML, its underlying concepts, its Levels-of-Detail, how to extend it, its applications, its likely future development, and the role it plays in scientific research. Furthermore, its relationship to other standards from the fields of computer graphics and computer-aided architectural design and to the prospective INSPIRE model are discussed, as well as the impact CityGML has and is having on the software industry, on applications of 3D city models, and on science generally.

Extended hybrid meshing algorithm for multiresolution terrain models

Hybrid terrains are a convenient approach for the representation of digital terrain models, integrating heterogeneous data from different sources. In this article, we present a general, efficient scheme for achieving interactive level-of-detail rendering of hybrid terrain models, without the need for a costly preprocessing or resampling of the original data. The presented method works with hybrid digital terrains combining regular grid data and local high-resolution triangulated irregular networks. Since grid and triangulated irregular network data may belong to different datasets, a straightforward combination of both geometries would lead to meshes with holes and overlapping triangles. Our method generates a single multiresolution model integrating the different parts in a coherent way, by performing an adaptive tessellation of the region between their boundaries. Hence, our solution is one of the few existing approaches for integrating different multiresolution algorithms within the same terrain model, achieving a simple interactive rendering of complex hybrid terrains.