无需人工干预的关节点提取和三维重建

随着现在人体的运动捕获和行为理解的研究的发展,对这项研究有了越来越高的要求。相对于原来的手动提取人体关节点作为特征点来研究,如何使得提取特征点更加自动化,对以后的运动捕获和行为理解的研究意义重大。提出一种在单目视觉条件下在第一帧自动提取人体关节点位置的方法,来解决传统的以手动标定提取人体关节点的问题,并且利用光流稀疏L_K算法 对提取出的关节点进行运动跟踪,得到运动人体二维坐标信息,结合像机模型通过几何计算获得人体关节点的深度信息。     

The indexing for one-dimensional proportionally-scaled strings

Related problems of scaled matching and indexing, which aim to determine all positions in a text T that a pattern P occurs in its scaled form, are considered important because of their applications to computer vision. However, previous results only focus on enlarged patterns, and do not allow shrunk patterns since they may disappear. In this paper, we give the definition and an efficient indexing algorithm for proportionally-scaled patterns that can be visually enlarged or shrunk. The proposed indexing algorithm takes O(|T|) time in its preprocessing phase, and achieves time in its answering phase, where |T|, |P|, Up, and m denote the length of T, the length of P, the number of reported positions, and the length of T under run-length representation, respectively.     

Bayesian analysis of robust Poisson geometric process model using heavy-tailed distributions

We propose a robust Poisson geometric process model with heavy-tailed distributions to cope with the problem of outliers as it may lead to an overestimation of mean and variance resulting in inaccurate interpretations of the situations. Two heavy-tailed distributions namely Student’s t and exponential power distributions with different tailednesses and kurtoses are used and they are represented in scale mixture of normal and scale mixture of uniform respectively. The proposed model is capable of describing the trend and meanwhile the mixing parameters in the scale mixture representations can detect the outlying observations. Simulations and real data analysis are performed to investigate the properties of the models.     

基于SIFT特征点匹配的水印图像几何校正算法*

为了有效实现水印图像的水印检测与水印嵌入之间的同步,提出一种应用SIFT(scale invariant feature transform)特征点匹配估计水印图像几何变换参数的校正算法.用两个稳定而又相距最远的图像SIFT特征点的变化估计图像所经历的旋转和缩放参数,校正之后,再用一个稳定的SIFT特征点的变化校正图像...     

分布式数据库研究的新方向

分布式数据库的研究已有二十余年历史。近年来半向何方发展 数据库的异构性与自治性,网络规模的膨胀以及移动计算技术的出现,都对分布式数据库技术提出新的挑战,本文从网络数据库的组织、等两个方面入手,讨论了分布式数据库研究所面临的几个新课题,最后对未来分布式数据库的发展前景作了展望。     

Numerical investigation of drag force on flow through circular array of cylinders

A 2-D model for flow through a circular patch with an array of vertical circular cylinders in a channel is established using the Navier-Stokes equations with a hybrid RANS/LES turbulence model–the Scale Adaptive Simulation (SAS) model. The applicability of the model is first validated by test cases where experimental data are available for comparison with the computed results. It is verified that the present model can predict well the average velocity and turbulence structure. The drag force and drag coefficient are then calculated using the present model for a number of cases with different solid volume fractions, cylinder Reynolds numbers and patch diameters. It is shown that the drag coefficient increases with increasing solid volume fraction, but decreases with increasing Reynolds number. However, the drag coefficient is independent of the diameter of circular batch when the solid volume fraction and Reynolds number are kept constant.     

基于Ncut的SIFT特征匹配算法

经典尺度不变特征变换(SIFT)特征匹配算法存在实时性差、纹理相似区域易发生误匹配的问题。为此,提出一种基于归一化分割(Ncut)的SIFT特征匹配算法。针对相同背景的运动视频,将归一化分割算法的图论聚类思想融入SIFT特征匹配中,根据运动趋势相似度对特征点进行Ncut运动聚类,再逐类分别匹配,通过缩小各特征点匹配过程中的搜索范围,减少匹配时间及不同特征类之间的误匹配。实验结果表明,该算法能提高匹配效率,对纹理相似区域的误匹配现象有较好的抑制作用,实现了相邻图像帧的特征稳定匹配。     

基于显著图的SIFT特征检测与匹配

基于尺度不变特征变换(SIFT)特征的图像匹配存在特征点数量大、运算时间长等问题。为此,引入视觉注意机制,提出一种基于显著图的SIFT特征检测与匹配方法。比较常用的显著图计算模型,选择谱残差方法提取图片的显著图。对显著图进行二值化和形态学等处理,得到规则合理的显著区域。在显著区域内提取SIFT特征,生成特征向量,进行图像匹配。实验结果表明,该方法能提高运算效率,并且得到的SIFT特征更加稳定。     

烟草制丝线电子皮带秤应用热点解析

为使烟草行业用户对电子皮带秤的招标技术要求更加合理,并为皮带秤制造厂商提供行业应用意见,对皮带秤的直接承重式结构、宽范围流量调节、6线制传感器、伺服电机、纠偏方法、校验方式、数据修饰等热点问题进行了分析。结果表明:目前直接承重式结构已适用于烟草行业皮带秤;实现宽流量范围不能忽略变速对计量精度的影响;6线制传感器和伺服电机仅在特定条件下才有必要使用;电动纠偏结合机械纠偏效果最好;抛码校验方式更适用;数据修饰无任何好处,反而易造成事故隐患。