Adaptive voxels: interactive rendering of massive 3D models

We present a novel approach for interactive rendering of massive 3D models. Our approach integrates adaptive sampling-based simplification, visibility culling, out-of-core data management and level-of-detail. We use a unified scene graph representation for acceleration techniques. In preprocessing, we subdivide large objects, and build a BVH clustering hierarchy. We make use of a novel adaptive sampling method to generate LOD models: AdaptiveVoxels. The AdaptiveVoxels reduces the preprocessing cost and our out-of-core rendering algorithm improves rendering efficiency. We have implemented our algorithm on a desktop PC. We can render massive CAD and isosurface models, consisting of hundreds of millions of triangles interactively with little loss in image quality.     

A Super-Resolution Framework for High-Accuracy Multiview Reconstruction

We present a variational framework to estimate super-resolved texture maps on a 3D geometry model of a surface from multiple images. Given the calibrated images and the reconstructed geometry, the proposed functional is convex in the super-resolution texture. Using a conformal atlas of the surface, we transform the model from the curved geometry to the flat charts and solve it using state-of-the-art and provably convergent primal–dual algorithms. In order to improve image alignment and quality of the texture, we extend the functional to also optimize for a normal displacement map on the surface as well as the camera calibration parameters. Since the sub-problems for displacement and camera parameters are non-convex, we revert to relaxation schemes in order to robustly estimate a minimizer via sequential convex programming. Experimental results confirm that the proposed super-resolution framework allows to recover textured models with significantly higher level-of-detail than the individual input images.     

A balanced decomposition approach to real-time visualization of large vector maps in CyberGIS

With the dramatic development of spatial data infrastructure, CyberGIS has become significant for geospatial data sharing. Due to the large number of concurrent users and large volume of vector data, CyberGIS faces a great challenge in how to improve performance. The real-time visualization of vector maps is themost common function in Cyber-GIS applications, and it is time-consuming especially when the data volume becomes large. So, how to improve the efficiency of visualization of large vector maps is still a significant research direction for GIScience scientists. In this research, we review the existing three optimization strategies, and determine that the third category strategy (i.e., parallel optimization) is appropriate for the real-time visualization of large vector maps. One of the key issues of parallel optimization is how to decompose the real-time visualization tasks into balanced sub tasks while taking into consideration the spatial heterogeneous characteristics. We put forward some rules that the decomposition should conform to, and design a real-time visualization framework for large vector maps. We focus on a balanced decomposition approach that can assure efficiency and effectiveness. Considering the spatial heterogeneous characteristic of vector data, we use a “horizontal grid, vertical multistage” approach to construct a spatial point distribution information grid. The load balancer analyzes the spatial characteristics of the map requests and decomposes the real-time viewshed into multiple balanced sub viewsheds. Then, all the sub viewsheds are distributed to multiple server nodes to be executed in parallel, so as to improve the realtime visualization efficiency of large vector maps. A group of experiments have been conducted by us. The analysis results demonstrate that the approach proposed in this research has the ability of balanced decomposition, and it is efficient and effective for all geometry types of vector data.     

Interactive display of large NURBS models

We present algorithms for interactive rendering of large-scale NURBS models. The algorithms convert the NURBS surfaces to Bezier surfaces, tessellate each Bezier surface into triangles, and render them using the triangle-rendering capabilities common to current graphics systems. We present algorithms for computing tight bounds on surface properties in order to generate high quality tessellation of Bezier surfaces. We introduce enhanced visibility determination techniques and present methods to make efficient use of coherence between successive frames. In addition, we also discuss issues in parallelization of these techniques. The algorithm also avoids polygonization anomalies like cracks. Our algorithms work well in practice and, on high-end graphics systems, are able to display models described using thousands of Bezier surfaces at interactive frame rates     

Compressed Facade Displacement Maps

We describe an approach to render massive urban models. To prevent a memory transfer bottleneck we propose to render the models from a compressed representation directly. Our solution is based on rendering crude building outlines as polygons and generating details by ray-tracing displacement maps in the fragment shader. We demonstrate how to compress a displacement map so that a decompression algorithm can selectively and quickly access individual entries in a fragment shader. Our prototype implementation shows how a massive urban model can be compressed by a factor of 85 and outperform a basic geometry-based renderer by a factor of 50 to 80 in rendering speed.     

Interactive level-of-detail selection using image-based quality metric for large volume visualization

For large volume visualization, an image-based quality metric is difficult to incorporate for level-of-detail selection and rendering without sacrificing the interactivity. This is because it is usually time-consuming to update view-dependent information as well as to adjust to transfer function changes. In this paper, we introduce an image-based level-of-detail selection algorithm for interactive visualization of large volumetric data. The design of our quality metric is based on an efficient way to evaluate the contribution of multiresolution data blocks to the final image. To ensure real-time update of the quality metric and interactive level-of-detail decisions, we propose a summary table scheme in response to runtime transfer function changes and a GPU-based solution for visibility estimation. Experimental results on large scientific and medical data sets demonstrate the effectiveness and efficiency of our algorithm     

Large‐Scale Pixel‐Precise Deferred Vector Maps

Rendering vector maps is a key challenge for high‐quality geographic visualization systems. In this paper, we present a novel approach to visualize vector maps over detailed terrain models in a pixel‐precise way. Our method proposes a deferred line rendering technique to display vector maps directly in a screen‐space shading stage over the 3D terrain visualization. Due to the absence of traditional geometric polygonal rendering, our algorithm is able to outperform conventional vector map rendering algorithms for geographic information systems, and supports advanced line anti‐aliasing as well as slope distortion correction. Furthermore, our deferred line rendering enables interactively customizable advanced vector styling methods as well as a tool for interactive pixel‐based editing operations.     

基于区域分解的并行动态LOD构建算法

面向大规模可视数据的高速绘制问题,提出了一种基于区域分解的并行动态LOD（level-of-detail,层次细节模型）构建算法。算法首先改进了传统的渐进网格方法,实现了基于二次误差测度网格简化算法的渐进网格方法;接着提出了一种基于模型包围盒的区域分解算法,实现了原始模型的自适应区域分解;在每个子区域上,并行地执行渐进网格方法,实现了模型的并行动态LOD构建。实验结果表明,该算法可生成高质量的LOD模型,具备理想的加速比和可扩放性;与串行算法相比,该算法有效地提高了算法的执行效率。     

Uniform remeshing with an adaptive domain: a new scheme for view-dependent level-of-detail rendering of meshes

We present a new algorithm for view-dependent level-of-detail rendering of meshes. Not only can it effectively resolve complex geometry features similar to edge collapse-based schemes, but it also produces meshes that modern graphics hardware can render efficiently. This is accomplished through a novel hybrid approach: for each frame, we view-dependently refine the progressive mesh (PM) representation of the original mesh and use the output as the base domain of uniform regular refinements. The algorithm exploits frame-to-frame coherence and only updates portions of the output mesh corresponding to modified domain triangles. The PM representation is built using a custom volume preservation-based error function. A simple k-d tree enhanced jump-and-walk scheme is used to quickly map from the dynamic base domain to the original mesh during regular refinements. In practice, the PM refinement provides a view-optimized base domain for later regular refinements. The regular refinements ensure almost-everywhere regularity of output meshes, allowing optimization for vertex cache coherence and caching of geometry data in high-performance graphics memory. Combined, they also have the effect of allowing our algorithm to operate on uniform clusters of triangles instead of individual ones, reducing CPU workload.     

Small target detection combining regional stability and saliency in a color image

In this paper, we will address the issue of detecting small target in a color image from the perspectives of both stability and saliency. First, we consider small target detection as a stable region extraction problem. Several stability criteria are applied to generate a stability map, which involves a set of locally stable regions derived from sequential boolean maps. Second, considering the local contrast of a small target and its surroundings, we obtain a saliency map by comparing the color vector of each pixel with its Gaussian blurred version. Finally, both the stability and saliency maps are integrated in a pixel-wise multiplication manner for removing false alarms. In addition, we introduce a set of integration models by combining several existing stability and saliency methods, and use them to indicate the validity of the proposed framework. Experimental results show that our model adapts to target size variations and performs favorably in terms of precision, recall and F-measure on three challenging datasets.     

基于矢量地图数据的异构混合快速绘制框架

随着测绘、遥感及相关技术的发展，矢量地图的数据规模和细节层次迅速增加，它们含有大量复杂的地理空间要素，且要素间存在复杂的拓扑几何关系，这使得大规模矢量地图的快速可视化对于高性能并行计算的需求十分迫切。针对这一问题，本文在原有的CPU多核处理的基础上引入GPU加速运算，提出一种基于CPU-GPU协同工作的异构混合并行绘制技术。实验结果表明，这种处理框架在矢量数据的快速可视化中作用较为显著，在大比例尺数据下并行加速比达到了较高的数值。     

3D map creation using crowdsourced GNSS data

3D maps are increasingly useful for many applications such as drone navigation, emergency services, and urban planning. However, creating 3D maps and keeping them up-to-date using existing technologies, such as laser scanners, is expensive. This paper proposes and implements a novel approach to generate 2.5D (otherwise known as 3D level-of-detail (LOD) 1) maps for free using Global Navigation Satellite Systems (GNSS) signals, which are globally available and are blocked only by obstacles between the satellites and the receivers. This enables us to find the patterns of GNSS signal availability and create 3D maps. The paper applies algorithms to GNSS signal strength patterns based on a boot-strapped technique that iteratively trains the signal classifiers while generating the map. Results of the proposed technique demonstrate the ability to create 3D maps using automatically processed GNSS data. The results show that the third dimension, i.e. height of the buildings, can be estimated with below 5 metre accuracy, which is the benchmark recommended by the CityGML standard.     

Sparse Local Submap Joining Filter for Building Large-Scale Maps

This paper presents a novel local submap joining algorithm for building large-scale feature-based maps: sparse local submap joining filter (SLSJF). The input to the filter is a sequence of local submaps. Each local submap is represented in a coordinate frame defined by the robot pose at which the map is initiated. The local submap state vector consists of the positions of all the local features and the final robot pose within the submap. The output of the filter is a global map containing the global positions of all the features as well as all the robot start/end poses of the local submaps. Use of an extended information filter (EIF) for fusing submaps makes the information matrix associated with SLSJF exactly sparse. The sparse structure together with a novel state vector and covariance submatrix recovery technique makes the SLSJF computationally very efficient. The SLSJF is a canonical and efficient submap joining solution for large-scale simultaneous localization and mapping (SLAM) problems that makes use of consistent local submaps generated by any reliable SLAM algorithm. The effectiveness and efficiency of the new algorithm is verified through computer simulations and experiments.      

Robocentric map joining: Improving the consistency of EKF-SLAM

In this paper¹ we study the Extended Kalman Filter approach to simultaneous localization and mapping (EKF-SLAM), describing its known properties and limitations, and concentrate on the filter consistency issue. We show that linearization of the inherent nonlinearities of both the vehicle motion and the sensor models frequently drives the solution of the EKF-SLAM out of consistency, specially in those situations where uncertainty surpasses a certain threshold. We propose a mapping algorithm, Robocentric Map Joining, which improves consistency of the EKF-SLAM algorithm by limiting the level of uncertainty in the continuous evolution of the stochastic map: (1) by building a sequence of independent local maps, and (2) by using a robot centered representation of each local map. Simulations and a large-scale indoor/outdoor experiment validate the proposed approach.     

Predicted Virtual Soft Shadow Maps with High Quality Filtering

In this paper we present a novel image based algorithm to render visually plausible anti‐aliased soft shadows in a robust and efficient manner. To achieve both high visual quality and high performance, it employs an accurate shadow map filtering method which guarantees smooth penumbrae and high quality anisotropic anti‐aliasing of the sharp transitions. Unlike approaches based on pre‐filtering approximations, our approach does not suffer from light bleeding or losing contact shadows. Discretization artefacts are avoided by creating virtual shadow maps on the fly according to a novel shadow map resolution prediction model. This model takes into account the screen space frequency of the penumbrae via a perceptual metric which has been directly established from an appropriate user study. Consequently, our algorithm always generates shadow maps with minimal resolutions enabling high performance while guarantying high quality. Thanks to this perceptual model, our algorithm can sometimes be faster at rendering soft shadows than hard shadows. It can render game‐like scenes at very high frame rates, and extremely large and complex scenes such as CAD models at interactive rates. In addition, our algorithm is highly scalable, and the quality versus performance trade‐off can be easily tweaked.     

FSAUA: A framework for sensitivity analysis and uncertainty assessment in historical and forecasted land use maps

Land change modelers often create future maps using reference land use map. However, future land use maps may mislead decision-makers, who are often unaware of the sensitivity and the uncertainty in land use maps due to error in data. Since most metrics that communicate uncertainty require using reference land use data to calculate accuracy, the assessment of uncertainty becomes challenging when no reference land use map for future is available. This study aims to develop a new conceptual framework for sensitivity analysis and uncertainty assessment (FSAUA) which compares multiple maps under various data error scenarios. FSAUA performs sensitivity analyses in land use maps using a reference map and assess uncertainty in predicted maps. FSAUA was applied using three well-known land change models (ANN, CART and MARS) in Delhi, India. FSAUA was found to be a practical tool for communicating the uncertainty with end-users who develop reliable planning decisions.     

矢量地图的无损数据隐藏算法研究

在矢量地图中隐含水印信息,地图数据的质量往往由于水印的嵌入而受到影响。可逆水印技术(又称无损数据隐藏)具有完整恢复载体数据的能力,因而更加适用于矢量地图。基于差值扩大的思想,提出了一种应用于矢量地图的无损数据隐藏算法。算法根据矢量地图对数据精度的特殊要求提出了相应的水印嵌入条件,并通过修改地图中相邻顶点坐标间的差值来嵌入水印信息。水印的提取过程不仅能够得到隐藏信息,而且能够准确无误地恢复原始地图数据。采用两类地图进行实验,实验结果表明,算法在具有较强坐标相关性的地图中具有较高的嵌入容量,并且引入较低的扰动。算法的应用前景包括矢量地图数据的篡改鉴别、元数据格式兼容以及基于矢量地图的隐藏通信。     

Adaptive Caustic Maps Using Deferred Shading

Caustic maps provide an interactive image-space method to render caustics, the focusing of light via reflection and refraction. Unfortunately, caustic mapping suffers problems similar to shadow mapping: aliasing from poor sampling and map projection as well as temporal incoherency from frame-to-frame sampling variations. To reduce these problems, researchers have suggested methods ranging from caustic blurring to building a multiresolution caustic map. Yet these all require a fixed photon sampling, precluding the use of importance-based photon densities. This paper introduces adaptive caustic maps. Instead of densely sampling photons via a rasterization pass, we adaptively emit photons using a deferred shading pass. We describe deferred rendering for refractive surfaces, which speeds rendering of refractive geometry up to 25% and with adaptive sampling speeds caustic rendering up to 200%. These benefits are particularly noticable for complex geometry or using millions of photons. While developed for a GPU rasterizer, adaptive caustic map creation can be performed by any renderer that individually traces photons, e.g., a GPU ray tracer.     

Filtered Stochastic Shadow Mapping Using a Layered Approach

Given a stochastic shadow map rendered with motion blur, our goal is to render an image from the eye with motion‐blurred shadows with as little noise as possible. We use a layered approach in the shadow map and reproject samples along the average motion vector, and then perform lookups in this representation. Our results include substantially improved shadow quality compared to previous work and a fast graphics processing unit (GPU) implementation. In addition, we devise a set of scenes that are designed to bring out and show problematic cases for motion‐blurred shadows. These scenes have difficult occlusion characteristics, and may be used in future research on this topic.