Automatic Creation of Object Hierarchies for Ray Tracing

Intersection calculations dominate the run time of canonical ray tracers. A common algorithm to reduce the number of intersection tests required is the intersection of rays with a tree of extents, rather than the whole database of objects. A shortcoming of this method is that these trees are difficult to generate. Additionally, manually generated trees can be poor, greatly reducing the run-time improvement available. We present methods for evaluation of these trees in approximate number of intersection calculations required and for automatic generation of good trees. These methods run in O(nlogn) expected time where n is the number of objects in the scene. We report some examples of speedups.     

A Practical Analysis of Clustering Strategies for Hierarchical Radiosity

The calculation of radiant energy balance in complex scenes has been made possible by hierarchical radiosity methods based on clustering mechanisms. Although clustering offers an elegant theoretical solution by reducing the asymptotic complexity of the algorithm, its practical use raises many difficulties, and may result in image artifacts or unexpected behavior. This paper proposes a detailed analysis of the expectations placed on clustering and compares the relative merits of existing, as well as newly introduced, clustering algorithms. This comparison starts from the precise definition of various clustering strategies based on a taxonomy of data structures and construction algorithms, and proceeds to an experimental study of the clustering behavior for real-world scenes. Interestingly, we observe that for some scenes light is difficult to simulate even with clustering. Our results lead to a series of observations characterizing the adequacy of clustering methods for meeting such diverse goals as progressive solution improvement, efficient ray casting acceleration, and faithful representation of object density for approximate visibility calculations.     

Automatic p-version mesh generation for curved domains

To achieve the exponential rates of convergence possible with the p-version finite element method requires properly constructed meshes. In the case of piecewise smooth domains, these meshes are characterized by having large curved elements over smooth portions of the domain and geometrically graded curved elements to isolate the edge and vertex singularities that are of interest. This paper presents a procedure under development for the automatic generation of such meshes for general three-dimensional domains defined in solid modeling systems. Two key steps in the procedure are the determination of the singular model edges and vertices, and the creation of geometrically graded elements around those entities. The other key step is the use of general curved element mesh modification procedures to correct any invalid elements created by the curving of mesh entities on the model boundary, which is required to ensure a properly geometric approximation of the domain. Example meshes are included to demonstrate the features of the procedure.

Automatic Hybrid Hierarchy Creation: a Cost-model Based Approach

While using hierarchical search structures has been proved as one of the most efficient acceleration techniques when rendering complex scenes, automatic creation of appropriate hierarchies is not solved yet. Well‐known algorithms for automatic creation of bounding volume hierarchies are not enough. Higher performance is achieved by introducing spatial uniform subdivision, although algorithms proposed up to now are not truly automatic, as they need some parameters to be adjusted. In this paper we present a full‐automatic hierarchy creation scheme that structures the scene in a hybrid way, combining bounding volumes and voxel grids in the same tree, selecting the search structure that best fits to each scene region. It uses no parameters at all. This efficient proposal relies on a new cost model that estimates the goodness of a hybrid hierarchy if used for rendering the scene. ACM CSS: I.3.7 Computer Graphics—Three‐Dimensional Graphics and Realism     

一种自动推断复杂系统层次结构任务模型的方法

支撑Internet服务的复杂系统难于调试与分析.理解系统运行时行为是调试与分析这些复杂系统的关键.现有的技术将系统动态运行时行为用因果执行路径抽象描述,并在此基础上分析系统的行为.但是这些方法或者需要手动标注系统代码,或者需要使用者描述系统的执行结构,都需要使用者很多人工辅助.文中描述了一种自动推断复杂系统层次结构任务模型的方法.通过使用插装技术动态观察系统执行过程,文中的方法能够根据一组启发自动推断出系统运行时的任务模型,包括任务的边界和任务之间的因果依赖关系.通过使用聚类方法,能够进一步推断出任务模型的层次结构.通过在实际系统(Apache和PacificA)上应用推断方法,可以看出,使用得到的模型能够帮助理解系统的动态运行过程,并帮助分析解决系统的性能问题.     

Object Clustering for High Performance Parallel Computing

In this article we present a new parallel programming environment, called distributed object-oriented virtual computing environment (DOVE), for clustered computers based on distributed object model. In DOVE, a parallel program is built as a collection of concurrent objects each of which has its own computing power and which interacts with one another by remote method invocation. The parallelism is encapsulated within distributed objects, which can be handled the same way as local objects. The main goal of DOVE is to provide users with an easy-to-use transparent parallel programming environment while supporting efficient parallelism encapsulated and distributed among objects. For the experiment and evaluation of DOVE, two parallel application programs have been developed both on DOVE and PVM.     

运算资源受限环境下的目标跟踪算法综述

自深度神经网络出现以来,目标跟踪技术领域的发展也取得了长足的进步。当前目标跟踪领域的研究大多数都集中在算力充沛的计算环境下提升算法的准确度与效率,在运算资源受限环境下的目标跟踪算法研究相对较少。因此,开发在运算资源受限环境下仍然有效的跟踪网络至关重要。对近年目标跟踪技术所取得的进展与设计理念进行了系统性的梳理,并总结其在适配运算资源受限环境下的改进。介绍了目标跟踪任务的整体工作流程,并根据各跟踪方法的侧重点做出归纳。总结了目标跟踪任务中已有的数据集与可用于模型评估的评价指标,以便于研究人员根据实际任务的需求来确定具体使用的数据集;结合现有的工作,发掘未来的研究方向。     

GLA聚类算法在视频对象提取中的应用

针对彩色视频对象提取,提出了基于GLA聚类算法对图像进行量化的方案。文中讨论了两种不同的GLS聚类方案,给出了各自的实现方案,并比较了结果。在具体实现时,根据人的视觉特性,采用了Lab彩色空间,并引入了PGF（同等组滤波）方法对图像进行噪声滤波,去除噪声的同时有效地保留了图像的边缘和细节信息。     

采用统计推断的自动视频对象分割

在新一代MPEG－4视频编码标准中,为了支持面向对象编码和实现基于内容的应用,视频对象（VO）的自动分割成为关键技术之一,减背景法是视频对象自动分割的基本方法,但是不同的环境光照条件常常给视频对象的分割带来困难,提出一种基于统计推断的减背景法。该方法首先建立背景统计模型,然后对后续帧进行假设检验,从而分割出视频对象。文中算法采用HSV颜色空间,通过对背景统计模型中各颜色分量的有效分析和区别使用,能够很好地适应不同的环境光照条件。实验表明,文中算法能够在各种光照环境下自动地实现视频对象的准确分割。     

室内人体运动目标的自动跟踪方法

针对人体运动目标的自动实时跟踪,设计一种新的基于P89v51内核的运动摄像头云台控制系统.对人体运动的图像检测与跟踪,提出一种快速的模板匹配方法.用改进Surendra算法自适应地获取背景图像以提取匹配模板,通过摄像头运动前后帧相同的运动区域来缩小匹配区域,进行快速目标匹配,达到实时性要求.该系统已应用在视频教学及会议中,实现自动人体运动目标跟踪与摄像.     

位相物体全息干涉计量的自动分析与处理

用全息干涉计量术对轴对称位相物体进行了测量，对测量结果用图象处理技术进行了自动分析与处理，指出在插值和反演计算中应注意的问题，提出采用“探索数”提取中心线的方法，提高了测量精度，最后给出计算结果。     

视频对象自动分割算法

提出了一种基于小波变换和运动边缘检测的自动视频对象分割方法。该方法对相邻帧分别进行二维小波变换，在小波域进行变化检测和Canny边缘提取，返回空间域后得到鲁棒的相邻帧差分边缘模板。结合当前帧边缘、背景边缘和前一帧的运动边缘，检测出当前帧对象的运动边缘，从而实现对视频对象的提取。通过实验验证，该算法对目标的整体运动和局部形变都有较强的适应性。此外，算法还具有快速、简便、准确性高的特点。     

Adaptive Grid Refinement Procedures for Efficient Optical Flow Computation

Two approaches are described that improve the efficiency of optical flow computation without incurring loss of accuracy. The first approach segments images into regions of moving objects. The method is based on a previously defined Galerkin finite element method on a triangular mesh combined with a multiresolution segmentation approach for object flow computation. Images are automatically segmented into subdomains of moving objects by an algorithm that employs a hierarchy of mesh coarseness for the flow computation, and these subdomains are reconstructed over a finer mesh on which to recompute flow more accurately. The second approach uses an adaptive mesh in which the resolution increases where motion is found to occur. Optical flow is computed over a reasonably coarse mesh, and this is used to construct an optimal adaptive mesh in a way that is different from the gradient methods reported in the literature. The finite element mesh facilitates a reduction in computational effort by enabling processing to focus on particular objects of interest in a scene (i.e. those areas where motion is detected). The proposed methods were tested on real and synthetic image sequences, and promising results are reported.     

自动确定聚类中心的快速搜索和发现密度峰值的聚类算法

快速搜索和发现密度峰值的聚类算法(CFSFDP)具有不能自动确定聚类中心的缺点,文中提出自动确定聚类中心的CFSFDP.首先针对变量分布不均匀的问题,将密度和距离进行归一化处理.再通过切比雪夫不等式确定归一化后的密度阈值上限,利用标准差确定归一化后的距离阈值上限.最后根据决策函数确定决策阈值上限,统筹考虑两种决定因素,避免中心点选取遗漏,自动确定聚类中心.实验表明,文中算法可以有效地自适应选择聚类中心,具有较好的鲁棒性和有效性.     

Efficient Geometry Compression for GPU-based Decoding in Realtime Terrain Rendering

We present a geometry compression scheme for restricted quadtree meshes and use this scheme for the compression of adaptively triangulated digital elevation models (DEMs). A compression factor of 8–9 is achieved by employing a generalized strip representation of quadtree meshes to incrementally encode vertex positions. In combination with adaptive error-controlled triangulation, this allows us to significantly reduce bandwidth requirements in the rendering of large DEMs that have to be paged from disk. The compression scheme is specifically tailored for GPU-based decoding, since it minimizes dependent memory access operations. We can thus trade CPU operations and CPU–GPU data transfer for GPU processing, resulting in twice faster streaming of DEMs from main memory into GPU memory. A novel storage format for decoded DEMs on the GPU facilitates a sustained rendering throughput of about 300 million triangles per second. Due to these properties, the proposed scheme enables scalable rendering with respect to the display resolution independent of the data size. For a maximum screen-space error below 1 pixel it achieves frame rates of over 100 fps, even on high-resolution displays. We validate the efficiency of the proposed method by presenting experimental results on scanned elevation models of several hundred gigabytes.     

基于对象组特征向量的聚类与分类的实现

高维稀疏数据的聚类分析是目前数据挖掘领域内亟待解决的问题之一。传统的聚类方法中,大部分不适用于高维稀疏数据,不能得到满意的结果。该文借助对象组相似度和对象组的特征向量,提出了一种实现聚类的方法。根据聚类结果后,根据聚类集合的上确界和下确界给出新对象的分类。该方法思想明了,实现起来简单轻松,结果准确可靠。     

A Point Symmetry-Based Clustering Technique for Automatic Evolution of Clusters

In this article, a new symmetry based genetic clustering algorithm is proposed which automatically evolves the number of clusters as well as the proper partitioning from a data set. Strings comprise both real numbers and the don't care symbol in order to encode a variable number of clusters. Here, assignment of points to different clusters are done based on a point symmetry based distance rather than the Euclidean distance. A newly proposed point symmetry based cluster validity index, {em Sym}-index, is used as a measure of the validity of the corresponding partitioning. The algorithm is therefore able to detect both convex and non-convex clusters irrespective of their sizes and shapes as long as they possess the point symmetry property. Kd-tree based nearest neighbor search is used to reduce the complexity of computing point symmetry based distance. A proof on the convergence property of variable string length GA with point symmetry based distance clustering (VGAPS-clustering) technique is also provided. The effectiveness of VGAPS-clustering compared to variable string length Genetic K-means algorithm (GCUK-clustering) and one recently developed weighted sum validity function based hybrid niching genetic algorithm (HNGA-clustering) is demonstrated for nine artificial and five real-life data sets.