考虑土体强度参数深度依赖性的非平稳随机场边坡滑动深度和体积分析

基于随机有限元方法（RFEM）和Monte-Carlo模拟,建立了能够模拟具有深度依赖性的土体强度参数边坡或具有软弱夹层边坡的非平稳随机场模型。通过辐射扫描方法获取最危险滑动面,得到非平稳随机场边坡滑动深度和滑动体积。将该方法与均质边坡和平稳随机场边坡获得的滑动深度和滑动体积进行对比,研究土体强度参数深度依赖性的非平稳随机场边坡的不同坡度和各向异性对滑动深度和滑动体积的影响。结果表明：基于RFEM的非平稳随机场滑动深度和滑动体积结果为地质灾害风险及后果评估提供了一个参考分析的新角度;参数的深度依赖性程度越高(变化率b越大),则边坡平均滑动深度和滑动体积越小;在大坡度滑坡风险后果评估中,可以基于均质边坡分析结果进行初步预估;在非平稳随机场中,随着各向异性的增大,所有坡度边坡的滑动体积变异系数增大;不同坡度下,水平方向的相关程度越大,则土坡内软弱夹层的不确定性越强,滑动体积的变异系数也不断增大。     

Order-k α-hulls and α-shapes

We introduce order-k α-hulls and α-shapes – generalizations of α-hulls and α-shapes. Being also a generalization of k-hull (known in statistics as “k-depth contour”), order-k α-hull provides a link between shape reconstruction and statistical depth. As a generalization of α-hull, order-k α-hull gives a robust shape estimation by ignoring locally up to k outliers in a point set. Order-k α-shape produces an “inner” shape of the set, with the amount of “digging” into the points controlled by k. As a generalization of k-hull, order-k α-hull is capable of determining “deep” points amidst samples from a multimodal distribution: it correctly identifies points which lie outside clusters of samples.The order-k α-hulls and α-shapes are related to order-k Voronoi diagrams in the same way in which α-hulls and α-shapes are related to Voronoi diagrams. This implies that order-k α-hull and α-shape can be readily built from order-k Voronoi diagram, and that the number of different order-k α-shapes for all possible values of α is proportional to the complexity of order-k Voronoi diagram.     

Bayesian estimation of Dirichlet mixture model with variational inference

In statistical modeling, parameter estimation is an essential and challengeable task. Estimation of the parameters in the Dirichlet mixture model (DMM) is analytically intractable, due to the integral expressions of the gamma function and its corresponding derivatives. We introduce a Bayesian estimation strategy to estimate the posterior distribution of the parameters in DMM. By assuming the gamma distribution as the prior to each parameter, we approximate both the prior and the posterior distribution of the parameters with a product of several mutually independent gamma distributions. The extended factorized approximation method is applied to introduce a single lower-bound to the variational objective function and an analytically tractable estimation solution is derived. Moreover, there is only one function that is maximized during iterations and, therefore, the convergence of the proposed algorithm is theoretically guaranteed. With synthesized data, the proposed method shows the advantages over the EM-based method and the previously proposed Bayesian estimation method. With two important multimedia signal processing applications, the good performance of the proposed Bayesian estimation method is demonstrated.     

护滩带边缘局部冲刷深度计算公式初步研究

长江航道整治工程广泛采用软体排护滩,简称护滩带,当护滩带边缘压载结构不同时,边缘外的局部冲刷会发生变化。采用水槽试验的方法,研究了不同压载体护滩带边缘的局部冲刷规律。研究发现,护滩带边缘冲刷深度随水流流速与泥沙起动流速之比的增加而增大;当排体外不铺设压载体时,排体上压载体透水率越大,局部冲刷深度也越大;当排体外铺设压载体时,局部冲刷深度随压载体铺设宽度的增大呈先减小,后变化不大的特点;当排体上压载体结构和排体外压载宽度相同时,排体外压载体透水率越大,局部冲刷深度也越大。依据试验资料,选取反映水流、河床及压载结构条件的因子,建立了具有一定精度的计算排体护滩带边缘局部冲刷深度的经验公式。     

泄水建筑物下游冲刷坑二维数值模拟

对巨亭水电站泄水建筑物下游局部冲刷过程进行了二维数值模拟。采用RNG k-ε湍流模型封闭N-S方程、有限体积法在计算网格上离散求解、VOF方法追踪自由水面;采用C语言编写用户自定义函数,以泥沙起动切应力作为床面泥沙起动判别标准,通过分析比较水流剪切力与泥沙起动切应力大小,用以控制冲刷坑底部边界变化;采用局部重构模型和弹簧光顺模型更新计算区域和网格质量,藉以模拟和追踪局部冲刷坑边界变化。研究表明,模拟结果与实测资料符合良好。在冲刷坑的冲刷过程中,床面剪切应力随着冲刷的进程急剧减小,湍动能随着冲刷的进程减小缓慢;床面剪切应力和湍动能沿程变化均较为剧烈,床面剪切应力沿程先增大后减小,床面湍动能则沿程减小。冲刷坑的纵向平衡形态或床面泥沙起动主要决定于床面剪切应力,床面湍动能对泥沙起动也具有重要影响。     

产品艺术形式的深度创新

文章对产品设计艺术形式的深度创新进行了分析与探索。选取家电、家居产品、五金产品、交通产品、数码电子产品中典型的中外设计案例,结合比较学的方法对优秀产品的深层创新与其它产品中的浅层创新做了比较分析。论述了产品设计中艺术形式创新应包含的本质内容。艺术形式深度创新的本质包括：为解决平凡生活中的某个问题而设计的形式;作为新技术的先导而设计的形式。研究的结论对减少资源浪费,提高人的生活质量,正确引导未来的设计走向具有重要意义。     

单幅图像多尺度小波深度提取算法

针对浅景深图像中平滑前景区域深度提取误差大的问题,基于像素点分类思想对深度值进行修正,提出一种基于多尺度小波线索的、可同时面向单幅浅景深图像和广角图像的深度图提取算法.首先使用小波分析法在多个尺度下提取图像深度信息;然后提出自适应分类法并根据尺度与深度变化规律对像素点做深度修正,得到深度图;最后结合区域生长与边缘分割算法对深度图进行区域优化.为了加快深度计算,还提出了快速zerocount法以及多尺度加速法来满足标清视频实时处理要求.实验结果证明,采用文中算法获得的深度图相对深度正确,前景和背景区域深度一致性好.     

kinect深度数据随机跳变误差分析及修正算法研究

采用微软空间扫描设备kinect的测距数据会产生随机跳变误差现象。通过分析误差原因及实验验证了跳变误差随距离增加曲线上升的特点。为修正该误差设计了一个基于像素滤波技术的误差修正算法。在kinect有效距离内连续观测三个待测物的空间深度数据和滤波数据。经实验验证在使用10帧深度数据可以将跳变误差在1.5m以内的跳变误差控制在5mm以内;1.5~3m以内的随机跳变误差控制大部分在10mm以内;超过3m的随机误差均匀分布在25mm以内。     

Aging and availability of binocular disparity and pictorial depth cues in 3D graphics contents

Some stereoblind observers do not perceive depth of 3D stimuli that depends on binocular disparity. These individuals, who have no disabilities, comprise over 5% of the general population. In addition, 17–30% of nonstereoblind young and young–middle people do not use disparity information in certain 3D environments, a phenomenon known as pseudo‐stereoblindness. This study aimed to investigate the relationship between aging and the proportion of pseudo‐stereoblindness in the general population. In an experiment, 134 nonstereoblind participants, ranging in age from 17 to 83 years, judged subjective depth of 3D stimuli containing binocular disparity and pictorial depth cues. Results showed that the proportion of pseudo‐stereoblindness among young (17–24 years old) and young–middle aged observers (25–39 years old) was 29%, in both cases. However, the proportion of pseudo‐stereoblind observers increased in older populations: 65% and 82% in the middle (40–54 years old) and senior (55–83 years old) age groups, respectively. These results suggest that a number of people, especially in elderly populations, have trouble perceiving depth from binocular disparity in 3D graphic contents despite their essential ability to use disparity information.     

Visual experience for autostereoscopic 3D projection display

In order to investigate visual experience for watching the autostereoscopic three‐dimensional (3D) projection display, we conduct a subjective evaluation experiment by a questionnaire when viewing video clips. Factor analysis is adopted to classify the evaluation items for the perpetual constructs of visual experience. Then a mixed design with repeated measurement analysis of variance with dimension and display duration as factors is carried out on the evaluation data to check the factorial effects and interactions for statistical significance. The results of factor analysis extract five factors including visual comfort, image quality, distortion, naturalness, and presence, which can be used as comprehensive indicators to evaluate the autostereoscopic 3D projection display. The results of analysis of variance indicate that image quality, which is used to assess two‐dimensional contents, is no longer applicable. It is necessary to give consideration to depth when evaluating 3D visual experience. Although 3D scenes enhance the overall subjective performance such as naturalness and presence, the health issues and stereoscopic distortion related to the introduction of depth cannot be ignored.