αB-spline: a linear singular blending B-spline

A linear singular blending (LSB) technique can enhance the shape—control capability of the B-spline. This capability is derived from the blending parameters defined at the B-spline control vertices and blends LSB line segments or bilinear surface patches with the B-spline curve or surface. Varying the blending parameters between zero and unity applies tension for reshaping. The reshaped curve or surface retains the same smoothness properties as the original B-spline; it possesses the same strict parametric continuities. This is different from the -spline, which introduces additional control to the B-spline by imposing geometrical continuities to the joints of curve segments or surface patches. For applications in which strict parametric continuities cannot be compromised, LSB provides an intuitive way to introduce tension to the B-spline.     

Quasiconvolutional smoothing of polyhedra

This paper describes a method for rounding edges and corners of arbitrary polyhedra that uses a fast approximation to convolutional filtering. The approximation defines an implicit surface, which is rendered with a specialised ray-tracing algorithm. By varying the radius of the smoothing filter, a wide range of effects can be obtained, from perfect polyhedra to blobby models. Small rounding radii give polyhedra a softer, more natural look, with edges well delineated by shadows and highlights. The rounded surfaces are much easier to specify and compute than those obtained by traditional filleting and surface-blending techniques, and are far more economical in storage.     

A portable stereo vision system for whole body surface imaging

This paper presents a whole body surface imaging system based on stereo vision technology. We have adopted a compact and economical configuration which involves only four stereo units to image the frontal and rear sides of the body. The success of the system depends on a stereo matching process that can effectively segment the body from the background in addition to recovering sufficient geometric details. For this purpose, we have developed a novel sub-pixel, dense stereo matching algorithm which includes two major phases. In the first phase, the foreground is accurately segmented with the help of a predefined virtual interface in the disparity space image, and a coarse disparity map is generated with block matching. In the second phase, local least squares matching is performed in combination with global optimization within a regularization framework, so as to ensure both accuracy and reliability. Our experimental results show that the system can realistically capture smooth and complete whole body shapes with high accuracy.     

Multi-sensor calibration through iterative registration and fusion

In this paper, a new multi-sensor calibration approach, called iterative registration and fusion (IRF), is presented. The key idea of this approach is to use surfaces reconstructed from multiple point clouds to enhance the registration accuracy and robustness. It calibrates the relative position and orientation of the spatial coordinate systems among multiple sensors by iteratively registering the discrete 3D sensor data against an evolving reconstructed B-spline surface, which results from the Kalman filter-based multi-sensor data fusion. Upon each registration, the sensor data gets closer to the surface. Upon fusing the newly registered sensor data with the surface, the updated surface represents the sensor data more accurately. We prove that such an iterative registration and fusion process is guaranteed to converge. We further demonstrate in experiments that the IRF can result in more accurate and more stable calibration than many classical point cloud registration methods.     

An Efficient Output-Size Sensitive Parallel Algorithm for Hidden-Surface Removal for Terrains

We describe an efficient parallel algorithm for hidden-surface removal for terrain maps. The algorithm runs in O(log ⁴ n) steps on the CREW PRAM model with a work bound of O((n+k) \polylog ( n)) where n and k are the input and output sizes, respectively. In order to achieve the work bound we use a number of techniques, among which our use of persistent data structures is somewhat novel in the context of parallel algorithms. Received July 29, 1998; revised October 5, 1999.     

露天磷矿数字配矿模型

露天磷矿选矿厂采用合理的配矿方案,对稳定入选磷矿的品位,增加选矿产率,降低生产成本有着重要的意义.为了提高入选磷矿石品位的均匀性和稳定性,提出了针对以入选磷矿品位为目标的从采矿场配矿到精矿仓配矿的整个生产环节的配矿方法.将采场内原矿、选矿厂原矿矿堆和选矿厂精矿仓均定义为矿堆,按照生产实际需求设定其属性.通过设定目标函数,实现使采矿场的开采原矿量最大,配矿方案总的运输距离最小,运输成本最低等目标.同时建立约束条件,使采矿场的开采原矿量要保证选矿厂正常生产,使每一矿堆的品位达到目标要求.最后,采集企业生产实际数据对模型加以验证,证明模型在指导露天磷矿山的生产过程中有重要的实际意义,配矿过程应成为矿山生产组织、管理的一个重要环节.     

应用MODIS资料对城乡地表热通量的估算

为了揭示城市热岛形成机制,基于MODIS资料,结合自动气象站实测的气象资料,利用地表能量参数化方法估算了地表热通量,分析了城乡地表热通量的空间分布及变化特征.结果表明城乡地气热交换差异明显,与相关文献对比证明该方法是可行、有效的.     

Applications of the Conjugate Gradient method in optimal surface parameterizations

This paper concerns the solutions of very large symmetric semipositive definite (singular) linear systems involved in the problem of optimal surface parameterizations using inverse curvature mapping. Two approaches are presented that transform the singular linear systems into two kinds of symmetric positive definite linear systems, so that the famous Conjugate Gradient (CG) method can be used for solving them. Numerical experiments are run on two practical large problems to illustrate that the CG algorithm works very efficiently.     

金属表面脏污区域的分割和量化算法研究

针对目前金属表面缺陷检测技术的研究现状,主要研究金属表面脏污检测与量化算法。结合金属表面的特点,通过对几种分割方法的比较,研究了阈值分割法中的迭代法对图像进行分割,该算法能够最大限度地保留细节信息。另外,研究了一种改进的自适应滤波算法结合像素计数法对金属表面的脏污区域进行量化处理。实验结果证明了所提出方法的有效性。