Optimizing BRDF orientations for the manipulation of anisotropic highlights

This paper introduces a system for the direct editing of highlights produced by anisotropic BRDFs, which we call anisotropic highlights. We first provide a comprehensive analysis of the link between the direction of anisotropy and the shape of highlight curves for arbitrary object surfaces. The gained insights provide the required ingredients to infer BRDF orientations from a prescribed highlight tangent field. This amounts to a non‐linear optimization problem, which is solved at interactive framerates during manipulation. Taking inspiration from sculpting software, we provide tools that give the impression of manipulating highlight curves while actually modifying their tangents. Our solver produces desired highlight shapes for a host of lighting environments and anisotropic BRDFs.     

A distributed solution to the network reconstruction problem

It has been recently shown in Ren et al. (2010) that by collecting noise-contaminated time series generated by a coupled-oscillator system at each node of a network, it is possible to robustly reconstruct its topology, i.e. determine the graph Laplacian. Restricting ourselves to linear consensus dynamics over undirected communication networks, in this paper we introduce a new dynamic average consensus least-squares algorithm to locally estimate these time series at each node, thus making the reconstruction process fully distributed and more easily applicable in the real world. We also propose a novel efficient method for separating the off-diagonal entries of the reconstructed Laplacian, and examine several concepts related to the trace of the dynamic correlation matrix of the coupled single integrators, which is a distinctive element of our network reconstruction method. The theory is illustrated with examples from computer, power and transportation systems.     

Continuous Levels‐of‐Detail and Visual Abstraction for Seamless Molecular Visualization

Molecular visualization is often challenged with rendering of large molecular structures in real time. We introduce a novel approach that enables us to show even large protein complexes. Our method is based on the level‐of‐detail concept, where we exploit three different abstractions combined in one visualization. Firstly, molecular surface abstraction exploits three different surfaces, solvent‐excluded surface (SES), Gaussian kernels and van der Waals spheres, combined as one surface by linear interpolation. Secondly, we introduce three shading abstraction levels and a method for creating seamless transitions between these representations. The SES representation with full shading and added contours stands in focus while on the other side a sphere representation of a cluster of atoms with constant shading and without contours provide the context. Thirdly, we propose a hierarchical abstraction based on a set of clusters formed on molecular atoms. All three abstraction models are driven by one importance function classifying the scene into the near‐, mid‐ and far‐field. Moreover, we introduce a methodology to render the entire molecule directly using the A‐buffer technique, which further improves the performance. The rendering performance is evaluated on series of molecules of varying atom counts.     

Approximations to auctions of digital goods with share-averse bidders

We consider the case of a digital product for share-averse bidders, where the product can be sold to multiple buyers who experience some disutility from other firms or consumers owning the same product. We model the problem of selling a digital product to share-averse bidders as an auction and apply a Bayesian optimal mechanism design. We also design constant-approximation algorithms in the prior-free setting including both average- and worst-case analyses.     

Online stiffness estimation for robotic tasks with force observers

In this paper we propose an online stiffness estimation technique for robotic tasks based only on force data, therefore, not requiring contact position information. This allows estimations to be obtained in robotic tasks involving interactions with unstructured and unknown environments where geometrical data is unavailable or unreliable. Our technique – the Candidate Observer Based Algorithm (COBA) – uses two force observers, configured with different candidate stiffnesses, to estimate online the actual target object stiffness. COBA is embedded in a force control architecture with computed torque in the task space. The theoretical presentation of the algorithm, as well as simulation tests and experimental results with a lightweight robot arm are also presented.     

一种基于图像匹配的地面交通标志实时识别方法

地面交通标志检测识别是智能驾驶领域的一个研究方向,实时性、准确率是该研究的重点。图像匹配的方法是常用的模式识别方法。文中介绍了一种结合先验知识和图像匹配的地面交通标志检测识别方法。算法包括两部分:预处理和检测识别。预处理阶段包括图像压缩、感兴趣区域提取、形态学处理、中值滤波和逆透视等步骤,实现图像降噪和正畸,为检测识别做准备。检测识别阶段包括轮廓提取、面积过滤、图像匹配等步骤,目的是判断待测图像是否含有地面交通标志及其种类。实验证明,该算法实时性好、鲁棒性强、准确率高。     

基于Snake的图像分割算法研究

图像分割算法是指从待割图像中提取出感兴趣的目标,以便进行图像分析与图像理解。Snake算法不同于传统的图像分割方法。文中详细介绍了Snake模型的数学机理及离散化方法,最后利用贪婪法实现了Snake算法,并应用与实际图像的分割。     

遗传算法理论及其应用研究进展

首先阐述遗传算法的原理和求解问题的一般过程;然后讨论了近年来从遗传算子、控制参数等方面对遗传算法的改进,并对遗传算法在计算机科学与人工智能、自动控制以及组合优化等领域的应用进行陈述;最后评述了遗传算法未来的研究方向和主要研究内容。     

利用ExcelVBA功能实现带照片证卡的及时打印

MS Excel内置了系统开发工具VBA可以方便地调用和定制主应用程序对象,用来扩展Microsoft Office应用程序功能。本文利用Excel及其函数和VBA的简单编程功能设计了学员证卡。使学员证卡实现现场采集照片、快速打印系统。     

长视距空战中可疑目标的快速识别模型仿真

研究长视距空战中可疑目标的快速识别问题,由于在长视距空战中,可疑目标与空中识别设备之间存在较长的距离,采集目标比较弱小,特征模糊.目标一旦过于接近,会形成堆积盲区,传统的识别方法在遇到远距离可疑目标时,由于距离太远,会出现目标堆积盲区,导致对目标分割出现错误,无法准确识别目标.为解决上述问题,提出采用主成分聚类算法的长视距空战中可疑目标的快速识别方法.针对可疑目标采集大量的计算机视觉图像,提取计算机视觉图像中可疑目标的特征,将上述特征作为可疑目标识别的依据.针对所有的可疑目标识别特征,进行可疑目标的快速识别,并对识别到的可疑目标进行累加运算,实现可疑目标的智能识别.实验结果表明,利用改进算法进行长视距空战中可疑目标的快速识别,能够极大的提高识别的准确性.