Polygon-based Method Research Articles

Improved rapid algorithm for continuous shading based on the fully analytical polygon-based method

The fully analytical polygon-based algorithm is an efficient and precise method for generating holograms. However, the method cannot directly incorporate rendering information. We adopt the framework of the fully analytical polygon-based algorithm and introduce an improved self-similar subdivision model to simplify the computation of pixel normal vectors in the Blinn-Phong lighting model. By decoupling the specular reflection component from the spectrum, the method elegantly avoids the issue of non-integrable exponents in the specular reflection term. Building upon previous research, we propose a new segmentation method that combines square and triangular segments to compute continuous shading. By reducing the number of segments, the proposed method can nearly double the computational efficiency while generating lighting effects for realistic scenes with specular highlights, thus reconstructing realistic 3D scenes. The effectiveness of the proposed method is validated through numerical simulations and optical reconstructions.

A Layered Method Based on Depth of Focus for Rapid Generation of Computer-Generated Holograms

In this paper, a layered method based on focal depth is proposed for the fast generation of computational holograms. The method layers objects with focal depth as spacing and approximates triangles on the object as projections on the layers based on the physical properties of the focal depth to simplify the computation. Finally, the diffraction distributions of all layers are calculated via angular spectral diffraction and superimposed to obtain the hologram. The proposed method has been proven to be about 20 times faster on a CPU than the analytical polygon-based method. A hologram containing tens of thousands of triangles can be computed on a GPU in a fraction of a second. In addition, this method makes it easy to attach complex textures, which is difficult with polygon-based analysis methods. Finally, holograms of objects with complex textures were generated, and the three-dimensionality of these holograms was confirmed by numerical and optical reconstruction.

Spatio-temporal characterization of drought variability in data-scarce regions using global precipitation data: a case study in Cauto river basin, Cuba.

Drought is considered the most severe water-related disaster in the Cauto river basin, which is the longest river and the main agricultural producer in Cuba. Better understanding of drought characteristics is crucial to drought management. Given the sparsity of ground-based precipitation observations in the Cauto, this study aims at using gridded global precipitation to analyze the spatio-temporal variations of drought in this river basin. Firstly, the monthly Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) was calibrated with the gauged precipitation using the Thiessen polygon-based method and linear least squares regression equations. Then, the gridded standardized precipitation index (SPI) with time scales of 3, 6, 9months and drought characteristics, namely, drought frequency, duration and intensity were calculated using the calibrated CHIRPS. Finally, the spatio-temporal analysis was performed to investigate the variations of drought in the Cauto river basin in time and space. The obtained results show that the calibrated CHIRPS is highly consistent with the gauged observations and is capable of determining the magnitude, time, and spatial extent of drought events in the Cauto river basin. The trend analysis by the Mann-Kendall test reveals that although the trend is not statistically significant, the SPI tends to decrease with time in the dry season, which indicates the more severe drought. The spatial analysis indicates that the lower altitude area of the Cauto river basin is suffered from longer drought duration and higher drought intensity than the upper one. This study expresses the importance of open global precipitation data sources in monitoring and quantifying drought characteristics in data-scarce regions.

Point-polygon hybrid method for generating holograms.

Computer-generated holograms (CGHs) are usually calculated from point clouds or polygon meshes. Point-based holograms are good at depicting details of objects, such as continuous depth cues, while polygon-based holograms tend to efficiently render high-density surfaces with accurate occlusions. Herein, we propose a novel point-polygon hybrid method (PPHM) to compute CGHs for the first time (to the best of our knowledge), which takes advantage of both point-based and polygon-based methods, and thus performs better than each of them separately. Reconstructions of 3D object holograms confirm that the proposed PPHM can present continuous depth cues with fewer triangles, implying high computational efficiency without losing quality.

High-speed rendering pipeline for polygon-based holograms

As an important three-dimensional (3D) display technology, computer-generated holograms (CGHs) have been facing challenges of computational efficiency and realism. The polygon-based method, as the mainstream CGH algorithm, has been widely studied and improved over the past 20 years. However, few comprehensive and high-speed methods have been proposed. In this study, we propose an analytical spectrum method based on the principle of spectral energy concentration, which can achieve a speedup of nearly 30 times and generate high-resolution (8K) holograms with low memory requirements. Based on the Phong illumination model and the sub-triangles method, we propose a shading rendering algorithm to achieve a very smooth and realistic reconstruction with only a small increase in computational effort. Benefiting from the idea of triangular subdivision and octree structures, the proposed original occlusion culling scheme can closely crop the overlapping areas with almost no additional overhead, thus rendering a 3D parallax sense. With this, we built a comprehensive high-speed rendering pipeline of polygon-based holograms capable of computing any complex 3D object. Numerical and optical reconstructions confirmed the generalizability of the pipeline.

An unsupervised framework for extracting multilane roads from OpenStreetMap

Multilane roads are a set of approximately parallel line segments representing the same road in large-scale vector maps. They must be extracted first in cartographic generalization. There are numerous multilane roads in the easily accessible OpenStreetMap (OSM) dataset. For this dataset, polygon-based methods have achieved state-of-the-art performance. However, traditional polygon-based methods usually rely on manually labeled data, which means they are time-consuming and labor-intensive. To address this problem, an unsupervised framework for extracting multilane roads is proposed in this study. Road segments were first grouped to form the road polygons. A set of shape descriptors was formulated to reduce the dimensions of individual road polygons into conceptual points. Next, dimensional shape descriptors were standardized using logarithmic standardization. The density peaks clustering (DPC) algorithm was employed to classify these points. Then, cluster tags were identified manually to recognize which clusters represent multilane polygons. Finally, post-processing learning from the concept of assimilation is proposed to fill holes and remove islands. Experiments were conducted to extract multilane roads with datasets from three cities: Wuhan, Beijing and Munich. The experimental results show that the proposed framework effectively extracted multilane roads without any labels with accuracy levels comparable to those of supervised methods.

Polygon-based computer-generated holography: a review of fundamentals and recent progress [Invited

In this review paper, we first provide comprehensive tutorials on two classical methods of polygon-based computer-generated holography: the traditional method (also called the fast-Fourier-transform-based method) and the analytical method. Indeed, other modern polygon-based methods build on the idea of the two methods. We will then present some selective methods with recent developments and progress and compare their computational reconstructions in terms of calculation speed and image quality, among other things. Finally, we discuss and propose a fast analytical method called the fast 3D affine transformation method, and based on the method, we present a numerical reconstruction of a computer-generated hologram (CGH) of a 3D surface consisting of 49,272 processed polygons of the face of a real person without the use of graphic processing units; to the best of our knowledge, this represents a state-of-the-art numerical result in polygon-based computed-generated holography. Finally, we also show optical reconstructions of such a CGH and another CGH of the Stanford bunny of 59,996 polygons with 31,724 processed polygons after back-face culling. We hope that this paper will bring out some of the essence of polygon-based computer-generated holography and provide some insights for future research.

Acceleration of polygon-based computer-generated holograms using look-up tables and reduction of the table size via principal component analysis.

In this study, we first analyze the fully analytical frequency spectrum solving method based on three-dimensional affine transform. Thus, we establish a new method for combining look-up tables (LUTs) with polygon holography. The proposed method was implemented and proved to be accelerated about twice compared to the existing methods. In addition, principal component analysis was used to compress the LUTs, effectively reducing the required memory without artifacts. Finally, we calculated very complex objects on a graphics processing unit using the proposed method, and the calculation speed was higher than that of existing polygon-based methods.

Representing Virtual Transparent Objects on Optical See-Through Head-Mounted Displays Based on Human Vision

In this study, we propose two methods for representing virtual transparent objects convincingly on an optical see-through head-mounted display without the use of an attenuation function or shielding environmental light. The first method represents the shadows and caustics of virtual transparent objects as illusionary images. Using this illusion-based approach, shadows can be represented without blocking the luminance produced by the real environment, and caustics are represented by adding the luminance of the environment to the produced shadow. In the second method, the visual effects that occur in each individual image of a transparent object are represented as surface, refraction, and reflection images by considering human binocular movement. The visual effects produced by this method reflect the disparities among the vergence and defocus of accommodation associated with the respective images. When reproducing the disparity, each parallax image is calculated in real time using a polygon-based method, whereas when reproducing the defocus, image processing is applied to blur each image and consider the user’s gaze image. To validate these approaches, we conducted experiments to evaluate the realism of the virtual transparent objects produced by each method. The results revealed that both methods produced virtual transparent objects with improved realism.

Zone division and extraction of historic area based on big data

ABSTRACT Although zoning has great potential in coordinating regional development and destination management, it is challenging to derive an optimal zoning method in the historic district. To address this challenge, this paper proposes a zone division method attempting to balance tourists’ and residents’ spatial demands and realizing urban historic area sustainable development. A 3-zones (Tourist active zone, Local community zone, and Buffer zone) plan is put forward based on a case study of the Qianmen area in Beijing, China. Then zone extraction is conducted with two kinds of big data, Points of Interests (POI) and Mobile Phone Signal (MPS). The Thiessen polygon-based method to divide the tourists’ concentrated area and a fishnet-based density method to distinguish the area of residents mainly living are used to help identify borderlines of different zones. A survey map for tourists and residents is used to verify the zone extraction results. Subsequently, zone management strategies are suggested for different zones improvement. This discussion contributes to overcoming the traditional methods’ defects in subarea-scale research with scientifically sound and practical.

Application Research on Computer Aided Simulation of Coastal Wetland Topography and Seawater Inundation Range

The computer-aided simulation of terrain optimization scheme can effectively solve the analysis problem of coastal wetland terrain and seawater inundation. The construction of three-dimensional model uses the traditional polygon-based method, which has great expression in terrain complexity and flexibility The limitations of voxel-based terrain production methods have brought various innovative ways to improve the quality of the 3D world scene while saving costs. A large part of the success of simulation technology now comes from the highly realistic 3D virtual world, which makes people immersed. And the application based on computer modeling can well meet the requirements of high-quality scenes. With the development and maturity of computer modeling technology, we are left with both opportunities and challenges. This article analyzes them.

Computerized quantification of pain drawings.

Background and aims Using a computer algorithm to quantify pain drawings could be useful, especially when large numbers of drawings need to be assessed. Whilst informal visual assessment of pain drawings can give clinicians a quick impression of the extent of pain and its location, formal quantification of pain drawings by computer for research purposes is not necessarily trivial. The current study compared seven different approaches to quantification in a large sample of clinical spinal pain drawings. Methods A large number (n = 55,720) of pain drawings were extracted from the SpineData database, a clinical registry of spinal pain patients in the Region of Southern Denmark. Drawings were analyzed both as pixel (raster) and vector based images, with different approaches based on the raw pain drawing, simple encircling polygons, convex-hull encircling polygons and discrete anatomical regions. Data were analyzed using principal component analysis, correlation and linear regression, as well as informal visual inspection of outlier pain drawings. Results Eighty-one percent of the variance could be explained by the first principal component, which we interpreted as the true score variance, i.e. the variance attributable to differences in pain area between individuals. The second principal component explained 10% of the variance and was loaded differentially by polygon-based methods and non-polygon-based methods. Correlations between the different approaches ranged from 0.66 to 1.00. Some approaches correlated so strongly as to be interchangeable, others tended to bias area estimates significantly. Visual inspection of outlier pain drawing indicated that when the different approaches to quantification yielded different results, characteristic patterns could be identified in the style and patterns of those pain drawings. Conclusions The different approaches reflected the same underlying construct (pain area), but could not be relied upon to produce the same area estimates and were affected by the interaction between drawing style and quantification approach. To some extend, the "correct" choice of quantification method is specific to and dictated by the style of each pain drawing. A differentiated approach is required in which the results of quantification and the drawing style are considered in combination. We provide suggestions for such differentiated approaches taking into account the nature of the drawing data (raster vs. vector) and the method of analysis (partly vs completely automated). Implications The chosen method of quantifying pain drawings in combination with the drawing style of the individual patient, can impact the resulting area estimate to a significant degree. These issues should be considered before undertaking computerized area estimation of pain drawings.

Influence of the Selection of Interpolation Method on Revealing Soil Organic Carbon Variability in the Red Soil Region, China

At present, various interpolation methods have been used for obtaining the spatial variability of soil organic carbon (SOC) in some regions. However, systematic research on accuracy comparison and the influence of method selection on revealing SOC variability is still lacking for the hilly red soil region of China. In this study, the spatial distributions of SOC were interpolated via three kriging methods (ordinary kriging (OK), kriging combined with soil type information (KSt), and with land-use information (KLu)) and three polygon-based methods (linking sample points data to the sampling grid (PGr), to soil type polygon (PSt), and to land-use polygon (PLu)) in Yujiang County, Jiangxi Province, China. To illustrate the influence of method selection on revealing SOC variability, the prediction efficiencies of these methods were compared with soil validation samples. The results showed that the KLu and PLu had high prediction accuracy, followed immediately by the KSt and PSt, while the OK and PGr had very low accuracies. Meanwhile, the SOC distribution contours obtained by KLu, PLu, KSt, and PSt could better reflect the real conditions of the study area, as they were consistent with the variation of land-use or soil types. However, the contours from the OK and PGr had poor performance with sketchy borderlines and regular homogeneous grid cells, respectively. Therefore, great differences exist in the prediction efficiency of different methods, and the interpolation method selection has an important impact on revealing SOC variability in the hilly red soil region of China. The results can provide a useful reference for the efficient SOC prediction and simulation in similar soil regions.

Applying rotation-invariant star descriptor to deep-sky image registration

Image registration is a critical process of many deep-sky image processing applications. Image registration methods include image stacking to reduce noise or achieve long exposure effects within a short exposure time, image stitching to extend the field of view, and atmospheric turbulence removal. The most widely used method for deep-sky image registration is the triangle- or polygon-based method, which is both memory and computation intensive. Deepsky image registration mainly focuses on translation and rotation caused by the vibration of imaging devices and the Earth’s rotation, where rotation is the more difficult problem. For this problem, the best method is to find corresponding rotation-invariant features between different images. In this paper, we analyze the defects introduced by applying rotation-invariant feature descriptors to deep-sky image registration and propose a novel descriptor. First, a dominant orientation is estimated from the geometrical relationships between a described star and two neighboring stable stars. An adaptive speeded-up robust features (SURF) descriptor is then constructed. During the construction of SURF, the local patch size adaptively changes based on the described star size. Finally, the proposed descriptor is formed by fusing star properties, geometrical relationships, and the adaptive SURF. Extensive experiments demonstrate that the proposed descriptor successfully addresses the gap resulting from applying the traditional feature-based method to deep-sky image registration and performs well compared to state-of-the-art descriptors.

GPU ray casting method for visualizing 3D pipelines in a virtual globe

ABSTRACTPipelines are an important part of urban infrastructure development. As part of a virtual globe (VG), the high-efficiency and high-quality visualization of 3D large-scale and high-density urban pipelines is of great importance. This paper proposes a GPU-based pipeline ray casting method for the visualization of urban-scale pipelines in the framework of a VG. The method involves the initial partitioning of the pipeline data into tiles, based on the relationship between the pipeline layer scale and the discrete global grid system (DGGSs). The pipeline centerline in each tile is then segmented and encoded, and a coarser pipeline bounding volume is subsequently constructed using a geometry shader. Finally, the fine 3D pipeline is rendered using a pixel shader. The results of the experimental implementation of the proposed method show that it satisfies the requirements for the multiscale visualization of pipelines in a VG. Moreover, compared with the traditional polygon-based method, the method facilitates a 20% increase in rendering frame rate for the same pixel level accuracy display effect. It also enables the visualization of the thickness of the 3D pipeline without any obvious effect on the rendering efficiency.

Holographic display methods for volume data: polygon-based and MIP-based methods.

Volume data are widely used in many areas, especially in biomedical science and geology. However, current visualization technologies of volume data cannot satisfy the visual requirements of humans. In this study, we propose two holographic display methods for volume data. The first method is polygon-based, and the other is maximum intensity projection (MIP)-based. Both methods are able to generate computer generated holograms of volume data. The polygon-based method can obtain various and colorful holograms, while the MIP-based method can be quickly calculated. Both methods can generate holographic animations, which were displayed on an electro-holography device.

Problems with reductive, polygon‐based methods for estimating species’ ranges: reply to Pimm et al. 2017

Problems with reductive, polygon‐based methods for estimating species’ ranges: reply to Pimm et al. 2017

Rendering of specular curved objects in polygon-based computer holography.

A realistic rendering technique is presented for creating large-scale computer-generated holograms. The technique is based on the polygon-based method, but allows specular curved surfaces to be reconstructed without increasing the number of polygons. In this technique, specular flat surfaces are transformed into curved surfaces. This is achieved by controlling the direction of reflected light, using fragmentary plane waves. An actual large-scale computer-generated hologram is created, and is used to verify the validity and practicality of the technique.

Improved polygon-based method for subwavelength pixel pitch computer generated holograms

An improved polygon-based method is proposed for subwavelength pixel pitch computer generated holograms (CGHs). By employing the basic principle of image-plane holograms, and by optimizing the parameters, objects are reconstructed with high quality from the CGHs whose pixel pitch is smaller than wavelength. It is believed that the proposed method is potentially promising for future large viewing angle holographic 3D displays.

A Comparative Study on Evaluation Methods of Fluid Forces on Cartesian Grids

We investigate the accuracy and the computational efficiency of the numerical schemes for evaluating fluid forces in Cartesian grid systems. A comparison is made between two different types of schemes, namely, polygon-based methods and mesh-based methods, which differ in the discretization of the surface of the object. The present assessment is intended to investigate the effects of the Reynolds number, the object motion, and the complexity of the object surface. The results show that the mesh-based methods work as well as the polygon-based methods, even if the object surface is discretized in a staircase manner. In addition, the results also show that the accuracy of the mesh-based methods is strongly dependent on the evaluation of shear stresses, and thus they must be evaluated by using a reliable method, such as the ghost-cell or ghost-fluid method.