基于层次分布域和粒子旋转的降雪模拟 *

传统降雪场景的模拟往往由于粒子数量的巨大而降低实时性。针对这一问题 ,在粒子系统的基础上采用梯形层次分布域来发射粒子 ,减少了不可见粒子的浪费 ;同时用伪粒子系统来体现粒子的旋转并引入了层叠纹理的方法来增加逼真度 ,在粒子的消亡条件判断上 ,采用部分判断的算法来提高实时性。实验表明 ,该方法能实时高效地绘制出较为真实的降雪现象。     

基于粒子系统的飘雪场景实时绘制

为了实现真实感飘雪场景特效,提出基于GPU加速的飘雪场景实时绘制方法。飘雪场景作为自然环境特效的一部分,一直是虚拟现实领域研究的难点。详细阐述基于GPU加速的飘雪场景实时绘制方法,包括雪粒子的产生、初始化、属性更新、沉积计算、消亡、绘制等过程。给出实验结果与分析,包括飘雪场景、飘雪效果、飘雪沉积等实验。实验证明,该方法是可行有效的。     

基于粒子系统和纹理绘制的火焰模拟

不规则物体的模拟一直是计算机图形学的研究热点和难点,而火焰在时间和空间上的多变性,更具有挑战性。本文详细讨论了火焰模型中火焰粒子属性的变化和纹理图片的选取。粒子系统是模拟不规则物体的有效方法,结合纹理映射增强绘制结果的真实感,可大大降低粒子数量,提高了绘制效率。实验表明,这种方法满足真实感和实时性的要求。     

基于OpenGVS战场火焰烟雾的模拟

战场特效有助于虚拟战场环境气氛的烘托,其模拟质量直接影响着整个战场仿真的质量.对于战场上的烟雾、火焰等不规则物体,不能采用传统的几何方法建模,而只能采用粒子系统等复杂的数学模型进行模拟.但在战场环境模拟时,同一场景中常常会出现多处火焰、烟雾的情况,这时巨大的计算量势必大大影响场景仿真的实时性.文章对基于OpenGVS的特效实现方法进行了研究,提出一种基于OpenGVS开发平台,将粒子系统模型与二维纹理动画模拟相结合的实现方式,明显减少了模拟所需计算量.将此方法运用到某型高炮训练仿真器的场景模拟中,实际应用表明,保证实时性的同时使战场特效得到了高质量的模拟.     

基于纹理滚动技术的多通道雨雪实时模拟

多通道技术是目前三维图形实时生成系统的一个重要发展方向,在多通道系统中模拟三维雨雪对实时性和通道间同步性有着较高的要求。在分析传统粒子系统生成方法的基础上,提出一种基于纹理滚动技术的雨雪模拟算法。基本思想是建立以视点为中心的多层圆柱面,以此为载体滚动雨雪纹理,并根据多层圆柱面间的深度差实现具有立体感的视差效果。实验证明,该方法能够生成逼真的视觉效果,并能较好地满足多通道系统的实时和通道间同步要求。     

基于纹理映射和粒子系统的三维喷泉实时模拟

将纹理映射和粒子系统理论相结合,给出一种基于粒子系统的喷泉系统模型,同时分析模型中粒子的属性及其变化,加入风力和阻力等粒子属性,绘制三维喷泉系统,实现粒子在复杂受力情况下的实时动态模拟.实验结果表明,该方法不仅有效地保证了图像的真实感,而且提高了系统的灵活性和实时性.     

基于 N-S 方程和纹理映射的实时火焰模拟

由于使用数学物理方法模拟火焰动画的计算量太大难以实现实时性,本文提出一种新的火焰模拟方法。该方法结合数学物理方法和粒子系统的优点,采用不可压缩的Navier-Stokes方程作为火焰模拟的物理模型,通过简化外力项的计算来提高计算速度。在渲染火焰时,提出一种新的基于纹理的火焰渲染方法来实现令人满意的火焰动画效果。实验基于OpenGL,以C＋＋编程,使用提出的方法成功实现火焰的实时模拟。     

基于视点的多分辨率纹理选择方法

MIP Mapping技术是纹理映射中一种有效的纹理反走样技术。但是MIP Mapping只是根据被渲染区域的大小来选择相应分辨率的纹理,在初始化的时候必须把所有的纹理细节层次调入内存,这种情况下会降低计算机的效率。提出了一种基于视点的三维地图控制方法,根据与视点相关的渲染区域大小以及视觉重要度来选择相应分辨率的纹理。试验证明该方法在不降低显示质量的同时能有效减少纹理的渲染量,提高了计算效率。     

基于粒子和纹理绘制的火焰合成

现有的火焰合成算法多数都是基于粒子系统,其主要缺点是运算量大。本文先用少量粒子勾勒火焰的外轮廓线,再用纹理绘制的方法填充火焰纹理。这样既利用了粒子系统形成轮廓线的真实感,又避免大量的粒子状态运算,并能体现动态火焰纹理的一致性和连续性。     

基于粒子数生成函数的烟雾模拟*

在大规模虚拟战场仿真和复杂环境仿真中,烟雾作为其中的重要组成部分,其模拟具有重要的意义。针对烟雾模拟中难以达到真实性和实时性平衡的问题,引入层次细节技术,减少了模拟中所需要的粒子数目,在满足视觉效果的前提下提高了实时性。引入改进的物理模型与粒子系统相结合,增强烟雾的细节,生成真实感较强的烟雾。此外,还利用烟气抬升高度的阈值控制法来判断粒子的生命情况,使烟雾的模拟更加真实。实验证明,本系统利用有限的粒子数生成了满足视觉真实性和视景系统实时性要求的烟雾场景。     

一种基于纹理测度的小波域数字水印模型

在图像数字水印技术中,采用JND阈值对水印的嵌入位置与强度进行控制,并在盲检测中作为搜索水印嵌入位置的依据,能够得到较理想的效果。JND阈值的鲁棒性对理想的盲检测结果至关重要。通过对数字水印系统的研究,提出了基于图像低频小波系数的定量纹理测度的JND阈值计算模型。该模型明显地提高了JND门限值的鲁棒性,即使在图像受到较大幅度改动的情况下,仍能很好地定位嵌入水印,从而有效地改善了盲检测的效果。同时给出了一种基于随机统计特征的匹配检测算法,该算法有效地提高了响应值,同时考虑响应值对应的虚警概率,从而使检测结果具有较强的说服力。     

基于 D3bQ15晶格离散三维风场的飘雪模拟 *

基于格子 BGK建立风场模型时 ,针对所用笛卡尔晶格的离散速度数少时 ,风场模型的数值精确度低 ;而离散速度数多时 ,计算速度慢的局限性 ,提出用体心立方晶格 D3bQ15离散三维风场。 D3bQ15晶格更好的各向同性及特定空间较少的采样数 ,调和了由离散速度数决定的风场模型的精确度与计算效率之间的矛盾。实验证明 :飘雪场景仿真中风场建模时 ,用 D3bQ15晶格比用笛卡尔晶格能更好地满足飘雪场景真实性和实时性的要求。     

Periodic pattern of texture analysis and synthesis based on texels distribution

Recently, sample-based texture synthesis techniques have drawn significant attention from researchers. These existing approaches mainly use the Markov Random Field (MRF) or texture features as texture model to analyze the local properties of sample textures. Indeed, human perception is sensitive to structure and periodicity. In this paper, we perform texture synthesis by taking into account the distribution of texels. Given a sample texture, the analysis procedure consists in segmenting texture into individual texels, and detecting each texel in order to analyze their neighborhood relationships by constructing connectivity. Then the synthesis process consists in reproducing a new large texture directly on a user-specified canvas by recomposing segmented texels, which synthesizes two-dimensional texel arrangements based on the previously constructed neighborhood relationships of texels. Results show that the proposed method is successful in generating textures visually indistinguishable to the sample textures. Moreover, the method especially deals with the near-regular textures, which well preserves underlying structural regularity.     

农业场景中下雪和积雪的实时模拟

下雪和积雪是农业场景中常见的自然现象.提出了一种下雪和积雪过程模拟的方法,算法采用粒子系统对雪粒子建模来模拟下雪过程,同时加入了风吹的效果.在模拟积雪时,通过在地面和屋顶构造一层三角形网格来保存雪的堆积信息,避免了保存雪粒子作为积雪实体的内存开销,同时考虑了雪飘落过程中与温室墙壁的碰撞检测.在渲染时,采用了平均法向量和混合顶点颜色的方法来获得平滑的效果.模拟结果表明,该方法能有效地再现农业场景中下雪和积雪场景,在满足实时交互漫游的前提下表现出较强的真实感.     

基于统计特征的DCT压缩域纹理图像检索方法

提出了一种基于离散余弦变换（Discrete Cosine Transfrom,DCT）的纹理图像的检索方法.该方法在DCT压缩域,通过直接对DCT系数计算,获得图像纹理的统计特征,并作为检索的依据.理论分析和实验结果都表明,该方法具有很好的检索准确率和效率,并且对于旋转具有不变性.     

Noise robust and rotation invariant texture classification based on local distribution transform

Multimedia Tools and Applications - Applying local binary pattern (LBP) to images with uniform distribution leads to generate discriminative features; however, the distribution of all images is not...     

A new approach for texture segmentation based on NBP method

Nowadays, image processing is an interesting research area due to the growth of the communication technologies. Matching problem, which consists of localizing one texture in an image, that contains several textures is one of the fundamental problem of image processing and pattern recognition. In this paper, a new feature extraction method and texture segmentation system are proposed. The proposed method (RINBP) is robust against rotation and improves the ability of extracting the local information. The segmentation architecture follows several steps. First, fixing a converging point α. After that, a Main analysis Window (MW) starting from α to the bottom left corner of the image is determined. Then, several possible windows are extracted and the feature extraction method is applied on each window. Finally, a similarity measure is calculated in order to decide if this window is pertinent or not. This process is stopped until the size of the MW reaches a minimum size. Each pertinent window increases the relevance of the desired texture in the output image. Finally, an image of relevance is obtained by considering the most relevant area. For the experiments, textured images generated from Brodatz album database are used. The experiments have shown the superiority of our method compared to other existing methods. The obtained results have illustrated the robustness and the efficiency of the proposed segmentation method based on the relevance of the analysis windows.     

A new texture representation approach based on local feature saliency

Although it has been studied in some depth, texture characterization is still a challenging issue for real-life applications. In this study, we propose a multiresolution salient-point-based approach in the wavelet domain. This incorporates a two-phase feature extraction scheme. In the first phase, each wavelet subband (LH, HL, or HH) is used to compute local features by using multidisciplined (statistical, geometrical, or fractal) existing texture measures. These features are converted into binary images, called salient point images (SPIs), via threshold operation. This operation is the key step in our approach because it provides an opportunity for better segmentation and combination of multiple features. In the final phase, we propose a set of new texture features, namely, salient-point density (SPD), non-salient-point density (NSPD), salient-point residual (SPR), saliency and non-saliency product (SNP), and salient-point distribution non-uniformity (SPDN). These features characterize various aspects of image texture such as fineness/coarseness, primitive distribution, internal structures, etc. These features are then applied to the well-known K-means algorithm for unsupervised segmentation of texture images. Experimental results with the standard texture (Brodatz) and natural images demonstrate the robustness and potential of the proposed features compared to the wavelet energy (WE) and local extrema density feature (LED). The text was submitted by the authors in English. Md. Khayrul Bashar was born in Chittagong, Bangladesh in 1969. He received his B.E. (1993), M.Tech. (1998), and PhD (2004) degrees from Bangladesh University of Engineering and Technology (BUET), Indian Institute of Technology (IIT) Bombay, and Nagoya University, respectively. He was a research engineer from 1995 to 1999 at Bangladesh Space Research and Remote Sensing Organization (SPARRSO) and assistant professor from 1999 to 2000 at the department of Electrical and Electronic Engineering, Chittagong University of Engineering and Technology (CUET), Bangladesh. Since 2004, he has been a research fellow in the department of Information Engineering, Nagoya University, Japan. Dr. Bashar is a member of IEEE, IEICE, BCS, and IEB. His research interest includes developing algorithms for image understanding, content-based image retrieval and web-application design, analysis and testing. Noboru Ohnishi was born in Aichi, Japan in 1951. He received his B.E., M.E., and PhD degrees in Electrical Engineering from Nagoya University in 1973, 1975, and 1984, respectively. From 1975–1986, he worked as a researcher in the Rehabilitation Engineering centre under the Ministry of Labor, Japan. In 1986, he joined as an Assistant Professor in the dept. of Electrical Engineering of Nagoya University. Currently, he is a professor of the dept. of Information Engineering at the same university. During his long professional life, he has also served as a visiting researcher (1992–1993) in the laboratory of artificial intelligence at Michigan University, and team leader (1993–2001) at the Bio-mimetic Control Research Center, RIKEN, Nagoya, Japan. He also holds many respectable positions at various professional bodies in Japan and he has published many research papers (more than 140) in various international journals. For his technical creativity and ingenuity, he was awarded SICE society prizes in 1996 and 1999. His research interest includes brain analysis, modeling, and brain support, computer vision, and audition. He is a member of IEEE, IPSJ, IEICE, IEEJ, IIITE, JNNS, SICE and RSJ. Kiyoshi Agusa received his PhD degree in computer science from Kyoto University in 1982. Currently, he is a professor of the department of Information Systems, Graduate School of Information Science, Nagoya University. His research area includes software engineering, program repository, and software reuse. Since 2003, he has been working as a team leader of a university-industry collaboration project entitled “e-Society,” which is a part of the “e-Japan” project, and doing research on reliability issues for web-based applications. He is a member of IPSJ, ISSST, IEICE, ACM and IEEE.