基于直方图插值的均值移动小尺寸目标跟踪算法

小尺寸目标跟踪是视觉跟踪中的难题。该文首先指出了均值移动小尺寸目标跟踪算法中的两个主要问题:算法跟踪中断和丢失跟踪目标。然后,论文给出了相应的解决方法。对传统Parzen窗密度估计法加以改进,并用于对候选目标区域的直方图进行插值处理,较好地解决了算法跟踪中断问题。论文采用Kullback-Leibler距离作为目标模型和候选目标之间的新型相似性度量函数,并推导了其相应的权值和新位置计算公式,提高了算法的跟踪精度。多段视频序列的跟踪实验表明,该文提出的算法可以有效地跟踪小尺寸目标,能够成功跟踪只有6×12个像素的小目标,跟踪精度也有一定提高。

形状填充率的物体识别算法

针对经典形状上下文算法对物体关节相对位置变化敏感的缺点,提出一种基于剪影局部形状填充率的物体识别算法.该算法以物体不同的轮廓控制点为圆心,计算不同半径下物体剪影像素所占总像素的比例,即为控制点的局部形状填充率;将不同控制点、不同半径长度所计算的形状填充率数值构成一个特征矩阵,该矩阵反映了物体整个剪影的统计特性.通过不同数据库的实验结果表明,文中算法对物体的细节有很强的描述能力,对物体关节的相对位置不敏感,并且受剪影轮廓控制点数量影响小.

Modeling, numerical methods, and simulation for particle-fluid two-phase flow problems

In this paper, we study the issues of modeling, numerical methods, and simulation with comparison to experimental data for the particle-fluid two-phase flow problem involving a solid-liquid mixed medium. The physical situation being considered is a pulsed liquid fluidized bed. The mathematical model is based on the assumption of one-dimensional flows, incompressible in both particle and fluid phases, equal particle diameters, and the wall friction force on both phases being ignored. The model consists of a set of coupled differential equations describing the conservation of mass and momentum in both phases with coupling and interaction between the two phases. We demonstrate conditions under which the system is either mathematically well posed or ill posed. We consider the general model with additional physical viscosities and/or additional virtual mass forces, both of which stabilize the system. Two numerical methods, one of them is first-order accurate and the other fifth-order accurate, are used to solve the models. A change of variable technique effectively handles the changing domain and boundary conditions. The numerical methods are demonstrated to be stable and convergent through careful numerical experiments. Simulation results for realistic pulsed liquid fluidized bed are provided and compared with experimental data. (C) 2004 Elsevier Ltd. All rights reserved.