Piecewise-Smooth Dense Optical Flow via Level Sets

We propose a new algorithm for dense optical flow computation. Dense optical flow schemes are challenged by the presence of motion discontinuities. In state of the art optical flow methods, over-smoothing of flow discontinuities accounts for most of the error. A breakthrough in the performance of optical flow computation has recently been achieved by Brox et~al. Our algorithm embeds their functional within a two phase active contour segmentation framework. Piecewise-smooth flow fields are accommodated and flow boundaries are crisp. Experimental results show the superiority of our algorithm with respect to alternative techniques. We also study a special case of optical flow computation, in which the camera is static. In this case we utilize a known background image to separate the moving elements in the sequence from the static elements. Tests with challenging real world sequences demonstrate the performance gains made possible by incorporating the static camera assumption in our algorithm.     

水平集曲线演化快速提取足迹轮廓

提出空间多分辨分析方法,通过分析图像行列方向能量投影的分布,将图像划分为大小不均匀的子块,根据图像的总体结构特征和局部细节特征自适应地调整子块大小,并以各子块的灰度均值作为新图像基元像素的灰度值,实现图像压缩.水平集曲线演化方法在压缩图像上进行,使得被处理的数据量大大减少,从而缩短了轮廓提取的时间,提高了算法的实用性.与边缘检测方法或直接水平集曲线演化方法相比较表明,该方法能够以较少的运算量获取较高的足迹轮廓提取准确度.     

语义转换--直接指称语义到接续指称语义

指称语义分为直接指称语义和接续指称语义,其中后一种语义描述的难度较大,给出了直接指称语义描述到接续指称语义描述的转换方法,这就使得这种语义转换的自动化成为可能．转换算法揭示了直接指称语义与接续指称语义之间的内在关系,同时也提供了写接续指称语义描述的有效方法．当需要检验同一种语言的直接指称语义描述和接续指称语义描述是否等价时,提供的技术是很有用的。     

Geometric Bone Modeling: From Macro to Micro Structures

There is major interest within the bio-engineering community in developing accurate and non-invasive means for visualizing, modeling and analyzing bone micro-structures. Bones are composed of hierarchical bio-composite materials characterized by complex multi-scale structural geometry. The process of reconstructing a volumetric bone model is usually based upon CT/MRI scanned images. Meshes generated by current commercial CAD systems cannot be used for further modeling or analysis. Moreover, recently develop...     

改进单纯形算法构造平面结晶体群动力系统的广义M集

针对逃逸时间算法计算量大，构图时间长的特点，本文提出了改进的有约束的单纯形最优化方法，求解了使平面结晶体群映射的Jacobin矩阵｜DF｜=0的点集作为初始迭代点集。由Lyapunov指数判定初始迭代点集的动力学特性，构造了平面结晶体群动力系统的广义M集．研究表明。运用改进的有约束的单纯形法构造非解析映射的广义M集这一方法是有效可行的，改进方法大大提高了平面结晶体群广义M集的构造速度．实现了对参数空间的有效划分．改进单纯形法构造的广义M集的混合区域更为准确地反映了相应动力平面上的动力学特性．     

辐射路匹配:从门级到功能模块级的子电路提取算法

提出一种基于子图同构的高性能辐射路匹配算法,以满足反向分析中逻辑综合的需要．通过单个顶点的相似度特征,将子图同构问题转化为顶点之间的匹配问题．在算法运行过程中,通过不断地删除搜索空间中的非匹配顶点,大大地降低了算法的时空复杂度．理论分析和实验结果表明,该算法的时空复杂度与目标电路的逻辑门数和功能模块电路的逻辑门数均为线性关系．     

广义Julia集关于迭代参数的对称性分析

由迭代函数fω,c(z)=zω c(ω∈C,c∈C)构造了广义Julia集(简称广义J集),并通过对迭代函数fω,c(z)=zω c(ω∈C,c∈C)中参数ω,c的改变,根据逃逸时间算法,利用VC 编程得到了相应的广义J集图形.通过图形对比,给出了仅随参数c变化所得图形对称性的一个重要结论,并从理论上给予了证明.类似地,通过对参数ω,c同时变化所得图形的分析,得到了相应的结论.     

From nonlinear to Hamiltonian via feedback

Mechanical control systems are an especially interesting and important class of nonlinear control systems. They possess a rich mathematical structure and yet, physical considerations are extremely important for the solution of a large class of control problems. We broaden the applicability of design methodologies developed for mechanical control systems by rendering nonlinear control systems, mechanical by a proper choice of feedback. In particular, we characterize which control systems can be transformed to Hamiltonian control systems by a feedback transformation.     

A Revisit of Shape Editing Techniques:From the Geometric to the Neural Viewpoint

3D shape editing is widely used in a range of applications such as movie production,computer games and computer aided design.It is also a popular research topic in computer graphics and computer vision.In past decades,researchers have developed a series of editing methods to make the editing process faster,more robust,and more reliable.Traditionally,the deformed shape is determined by the optimal transformation and weights for an energy formulation.With increasing availability of 3D shapes on the Internet,data-driven methods were proposed to improve the editing results.More recently as the deep neural networks became popular,many deep learning based editing methods have been developed in this field,which are naturally data-driven.We mainly survey recent research studies from the geometric viewpoint to those emerging neural deformation techniques and categorize them into organic shape editing methods and man-made model editing methods.Both traditional methods and recent neural network based methods are reviewed.     

Story Albums: Creating Fictional Stories From Personal Photograph Sets

We present a method for the automatic creation of fictional storybooks based on personal photographs. Unlike previous attempts that summarize such collections by picking salient or diverse photos, or creating personal literal narratives, we focus on the creation of fictional stories. This provides new value to users, as well as an engaging way for people (especially children) to experience their own photographs. We use a graph model to represent an artist‐generated story, where each node is a ‘frame’, akin to frames in comics or storyboards. A node is described by story elements, comprising actors, location, supporting objects and time. The edges in the graph encode connections between these elements and provide the discourse of the story. Based on this construction, we develop a constraint satisfaction algorithm for one‐to‐one assignment of nodes to photographs. Once each node is assigned to a photograph, a visual depiction of the story can be generated in different styles using various templates. We show results of several fictional visual stories created from different personal photo sets and in different styles.     

New approach to analysis and optimal control of time-varying systems via Taylor series

A new approach with three novel operations is proposed to deal with analysis of linear and bilinear time-varying systems and optimal control of linear time-varying systems via the Taylor series. The use of the three operations: polynomial mapping, general multiplication and integral transformer can greatly simplify the algorithm derivations and computations. Recursive algorithms are obtained and several illustrative examples are given.     

文脉视阈下的江南室内空间地域性符号的延续与更新

设计趋同化使得室内空间呈现"大同之世",室内空间的地域性特征在逐步消失,而随着人们生活水平及文化水平的提高,人们又向往那些能够体现地域化特征的室内空间,也是人们从物质文化提升到非物质文化的一种体现。文章将从设计符号学的角度入手,提取江南室内空间中对于体现江南地域性特征的符号元素,运用设计符号学的创新法则——文脉原则,浅析江南室内空间地域性符号的延续与更新,达到一种古为今用,意在创新的继承与发展,复苏逐渐失去地域性特征的江南室内空间设计。     

Non-Parametric Mixture Model Based Evolution of Level Sets and Application to Medical Images

We present a novel region-based curve evolution algorithm which has three primary contributions: (i) non-parametric estimation of probability distributions using the recently developed NP windows method; (ii) an inequality-constrained least squares method to model the image histogram with a mixture of nonparametric probability distributions; and (iii) accommodation of the partial volume effect, which is primarily due to low resolution images, and which often poses a significant challenge in medical image analysis (our primary application area). We first approximate the image intensity histogram as a mixture of non-parametric probability density functions (PDFs), justifying its use with respect to medical image analysis. The individual densities in the mixture are estimated using the recent NP windows PDF estimation method, which builds a continuous representation of discrete signals. A Bayesian framework is then formulated in which likelihood probabilities are given by the non-parametric PDFs and prior probabilities are calculated using an inequality constrained least squares method. The non-parametric PDFs are then learnt and the segmentation solution is spatially regularised using a level sets framework. The log ratio of the posterior probabilities is used to drive the level set evolution. As background to our approach, we recall related developments in level set methods. Results are presented for a set of synthetic and natural images as well as simulated and real medical images of various anatomical organs. Results on a range of images show the effectiveness of the proposed algorithm.     

From control law diagrams to Ada via Circus

Control engineers make extensive use of diagrammatic notations; control law diagrams are used in industry every day. Techniques and tools for analysis of these diagrams or their models are plentiful, but verification of their implementations is a challenge that has been taken up by few. We are aware only of approaches that rely on automatic code generation, which is not enough assurance for certification, and often not adequate when tailored hardware components are used. Our work is based on Circus, a notation that combines Z, CSP, and a refinement calculus, and on industrial tools that produce partial Z and CSP models of discrete-time Simulink diagrams. We present a strategy to translate Simulink diagrams to Circus, and a strategy to prove that a parallel Ada implementation refines the Circus specification; we rely on a Circus semantics for the program. By using a combined notation, we provide a specification that considers both functional and behavioural aspects of a large set of diagrams, and support verification of a large number of implementations. We can handle, for instance, arbitrarily large data types and dynamic scheduling.     

From Web Data to Visualization via Ontology Mapping

In this paper, we propose a novel approach for automatic generation of visualizations from domain‐specific data available on the web. We describe a general system pipeline that combines ontology mapping and probabilistic reasoning techniques. With this approach, a web page is first mapped to a Domain Ontology, which stores the semantics of a specific subject domain (e.g., music charts). The Domain Ontology is then mapped to one or more Visual Representation Ontologies, each of which captures the semantics of a visualization style (e.g., tree maps). To enable the mapping between these two ontologies, we establish a Semantic Bridging Ontology, which specifies the appropriateness of each semantic bridge. Finally each Visual Representation Ontology is mapped to a visualization using an external visualization toolkit. Using this approach, we have developed a prototype software tool, SemViz, as a realisation of this approach. By interfacing its Visual Representation Ontologies with public domain software such as ILOG Discovery and Prefuse, SemViz is able to generate appropriate visualizations automatically from a large collection of popular web pages for music charts without prior knowledge of these web pages.     

An effective approach to the optimal-control problem for time-varying linear systems via Taylor series

The Taylor series is used for the solution of the optimal-control problem for time-varying linear systems. Instead of solving the state transition matrix from the state equation with a terminal condition, the present approach first transforms the terminal condition into an initial condition, and then solves the initial-value problem to find the transition matrix. This approach leads lo a recursive algebraic formulation for the transition matrix, and only an inverse matrix of small dimension 2n × 2n appears in this formulation. Thus a closed-loop control law is obtained without solving the non-linear Riccati equation, and the matrix to be inverted has only small dimension 2n × 2n. The present approach is of great interest because of its simplicity and numerical stability.