Reconstruction of Images-- Realistic Oil Paintings

UIUC汽车检测图像数据库(UIUC Image Database for Car Detection)

UIUC汽车检测图像数据库(UIUC Image Database for Car Detection) 数据介绍： This database contains images of side views of cars for use in evaluating object detection algorithms. 关键词：汽车,探测,目标检测算法,目标,算法, cars,car,detection,object detection algorithms,object,algorithms,algorithm, 数据格式： TEXT 数据详细介绍： UIUC Image Database for Car Detection ●Description This database contains images of side views of cars for use in evaluating object detection algorithms. The images were collected at UIUC by Shivani Agarwal, Aatif Awan and Dan Roth, and were used in the experiments reported in [1], [2]. ●Data information The download package contains the following: 1050 training images (550 car and 500 non-car images) 170 single-scale test images, containing 200 cars at roughly the same scale as in the training images 108 multi-scale test images, containing 139 cars at various scales

运筹学课程设计指导书

运筹学课程设计指导书一、课程设计目的 1、初步掌握运筹学知识在管理问题中应用的基本方法与步骤； 2、巩固和加深对所学运筹学理论知识及方法的理解与掌握； 3、锻炼从管理实践中发掘、提炼问题，分析问题，选择建立运筹学模型，利用模型求解问题，并对问题的解进行分析与评价的综合应用能力； 4、通过利用运筹学计算机软件求解模型的操作，掌握运筹学计算软件的基本操作方法，并了解计算机在运筹学中的应用；二、课程设计内容与步骤第一部分是基本实验，为必做部分；需要每位同学单独完成，并写出相应的实验报告。第二部分是提高部分，题目自选或自拟，锻炼综合应用运筹学知识及软件解决实际问题的能力；可以单独完成，也可以合作完成（最多3人一组），写出相应的报告。 1、基本实验在完成基本实验后，每位同学要按照实验要求完成实验报告，实验报告应包括问题描述、建模、上机求解、结果分析及答辩几方面。实验报告必须是打印稿（word文档等），手写稿无效。请大家按照要求认真完成实验报告，如果两份实验报告雷同，或相差很少，则两份实验报告均为0分，其它抄袭情况，将根据抄袭多少扣分。（约占总分的70%） 2、提高部分根据自己的兴趣或所查找的资料，从实际情况出发，自拟题目；在实验报告中，陈述问题，建立模型，求解，结果分析，此部分应着重突出自己的观点和想法。（此部分按照排名先后给分，约占总分的30%）三、课程设计要求 1、实验目的学会建立相应的运筹学模型学会Excel、Lindo和WinQSB，QM for windows软件的基本使用方法学会用Excel、Lindo和WinQSB，QM for windows软件得到问题的最优解 2、实验要求分析问题、建立模型,并阐明建立模型的过程；说明并显示软件使用和计算的详细过程与结果；结果分析,将结果返回到实际问题进行分析、评价。四、题目内容（一）Excel规划求解基本实验 1、雅致家具厂生产4种小型家具，由于该四种家具具有不同的大小、形状、重量和风格，所以它们所需要的主要原料（木材和玻璃）、制作时间、最大销售量与利润均不相同。该厂每天可提供的木材、玻璃和工人劳动时间分别为600单位、1000单位与400小时，详细的数据资料见下表。问：（1）应如何安排这四种家具的日产量，使得该厂的日利润最大？（2）家具厂是否愿意出10元的加班费，让某工人加班1小时？（3）如果可提供的工人劳动时间变为398小时，该厂的日利润有何变化？（4）该厂应优先考虑购买何种资源？

Hybrid images

Copyright ? 2006 by the Association for Computing Machinery, Inc. Permission to make digital or hard c opies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for c ommercial advantage and that c opies bear this notic e and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior spec ific permission and/or a fee. Request permissions from Permissions Dept, ACM Inc., fax +1 (212) 869-0481 or e-mail permissions@https://www.360docs.net/doc/882058088.html, . ? 2006 ACM 0730-0301/06/0700- $5.00 0527Hybrid images Aude Oliva ?MIT-BCS Antonio Torralba ?MIT-CSAIL Philippe.G.Schyns ?University of Glasgow Figure 1:A hybrid image is a picture that combines the low-spatial frequencies of one picture with the high spatial frequencies of another picture producing an image with an interpretation that changes with viewing distance.In this ?gure,the people may appear sad,up close,but step back a few meters and look at the expressions again. Abstract We present hybrid images ,a technique that produces static images with two interpretations,which change as a function of viewing distance.Hybrid images are based on the multiscale processing of images by the human visual system and are motivated by masking studies in visual perception.These images can be used to create compelling displays in which the image appears to change as the viewing distance changes.We show that by taking into account perceptual grouping mechanisms it is possible to build compelling hybrid images with stable percepts at each distance.We show ex-amples in which hybrid images are used to create textures that be-come visible only when seen up-close,to generate facial expres-sions whose interpretation changes with viewing distance,and to visualize changes over time within a single picture.Keywords:Hybrid images,human perception,scale space 1Introduction Here we exploit the multiscale perceptual mechanisms of human vi-sion to create visual illusions (hybrid images )where two different interpretations of a picture can be perceived by changing the view-ing distance or the presentation time.We use and extend the method originally proposed by Schyns and Oliva [1994;1997;1999].Fig.1shows an example of a hybrid image assembled from two images ?e-mail:oliva@https://www.360docs.net/doc/882058088.html, ?e-mail:torralba@https://www.360docs.net/doc/882058088.html, ?e-mail: p.schyns@https://www.360docs.net/doc/882058088.html, in which the faces displayed different emotions.High spatial fre-quencies correspond to faces with ”sad”expressions.Low spatial frequencies correspond to the same faces with ”happy”and ”sur-prise”emotions (i.e.,the emotions are,from left to right:happy,surprise,happy and happy).To switch from one interpretation to the other one can step away a few meters from the picture.Artists have effectively employed low spatial frequency manipu-lation to elicit a percept that changes when relying on peripheral vision (e.g.,[Livingstone 2000;Dali 1996]).Inspired by this work,Setlur and Gooch [2004]propose a technique that creates facial im-ages with con?icting emotional states at different spatial frequen-cies.The images produce subtle expression variations with gaze changes.In this paper,we demonstrate the effectiveness of hybrid images in creating images with two very different possible interpre-tations. Hybrid images are generated by superimposing two images at two different spatial scales:the low-spatial scale is obtained by ?ltering one image with a low-pass ?lter;the high spatial scale is obtained by ?ltering a second image with a high-pass ?lter.The ?nal im-age is composed by adding these two ?ltered images.Note that hybrid images are a different technique than picture mosaics [Sil-vers 1997].Picture mosaics have two interpretations:a local one (which is given by the content of each of the pictures that compose the mosaic)and a global one (which is best seen at some prede?ned distance).Hybrid images,however,contain two coherent global image interpretations,one of which is of the low spatial frequen-cies,the other of high spatial frequencies. We illustrate this technique with several proof-of-concept exam-ples.We show how this technique can be applied to create face pictures that change expression with viewing distance,to display two con?gurations of a scene in a single picture,and to present tex-tures that disappear when viewed at a distance. 2The design of hybrid images A hybrid image (H )is obtained by combining two images (I 1and I 2),one ?ltered with a low-pass ?lter (G 1)and the second one ?l-

MATLAB与在运筹学中的应用

MATLAB与在运筹学中的应用摘要：论文通过MATLAB在运筹学中的应用实例，探讨了MATLAB在运筹学中的应用方法和技巧，初步了解matlab中优化工具箱的使用。关键字：MATLAB应用运筹学优化计算引言运筹学是近代应用数学的一个分支，主要是研究如何将生产、管理等事件中出现的运筹问题加以提炼，然后利用数学方法进行解决的学科。运筹学是应用数学和形式科学的跨领域研究，利用像是统计学、数学模型和算法等方法，去寻找复杂问题中的最佳或近似最佳的解答。运筹学经常用于解决现实生活中的复杂问题，特别是改善或优化现有系统的效率。运筹学中常用的运算工具有Matlab、Mathematica、Maple、SAS 、SPSS、Lindo/Lingo、GAMS、WinQSB、Excel、其他，如SQP、DPS、ORS、Visual Decision、Decision Explore、AIMMS、Crystal等。 Matlab是矩阵实验室（Matrix Laboratory）的简称，是美国MathWorks公司出品的商业数学软件，和Mathematica、Maple并称为三大数学软件。用于算法开发、数据可视化、数据分析以及数值计算的高级技术计算语言和交互式环境，主要包括Matlab和Simulink两大部分。主要应用于工程计算、控制设计、信号处理与通讯、图像处理、信号检测、金融建模设计与分析等领域。将matlab用于运筹学的最优化运算可以很好的解决优化问题，而且matlab 还专门有优化工具箱，是处理优化问题更加方便。一、例：0-1规划（《运筹学》80页例3-9）求minZ=x1-3*x2+6*x3+2*x4-4*x5 6*x1+2*x2-x3+7*x4+x5<=12 约束条件 x1+4*x2+5*x3-x4+3*x5>=10 Xj=0或1，j=1,2,3,4

运用线性规划对运输问题研究

运用线性规划对运输问题研究班级：金融103班姓名：王纬福学号：5400210132摘要：由于企业选择运输路线或运输工具不合理而导致物流运输成本不能最小化的问题普遍存在而管理运筹学却能很好的解决此问题。通过科学的方法对问题进行具体化再建立数学模型并求解，就能找到运输成本最小的运输组合。关键词：物流运输成本、输成本、管理运筹学、WinQSB2.0、线性规划一、引言日常生活中，人们经常需要将某些物品由一个空间位置移动到另一个空间位置，这就产生了运输。如何判定科学的运输方案，使运输所需的总费用最少，就是管理运筹学在运输问题上的运用需要解决的问题。运输问题是一类应用广泛的特殊的线性规划问题，在线性规划的一般理论和单纯形法出现以前，康托洛维奇（L.V.Kant）和希奇柯克（F.L.Hitchcock）已经研究了运输问题。所以，运输问题又有“康-希问题”之称。对于运输问题（Transportation Problem TP）当然可用前面所讲的单纯形法求解，但由于该问题本身的特殊性，我们可以找到比标准单纯形法更简单有效的专门方法，从而节约计算时间和费用。主要是因为它们的约束方程组的系数矩阵具有特殊结构，使得这类问题的求解方法比常规的单纯形法要更为简便。一、研究现状运输问题的研究较多，并且几乎所有的线性规划书中都有论述。遗憾的是一些书中所建立的数学模型都不够全面和系统的。但是也有一些模型是严谨的没有漏洞和缺陷，并且很容易在此基础上修改或添加一些其他约束条件便于在实际工程中进行应用。管理运筹学在运输问题上的研究较为深入、全面、系统。对于计算机软件的引用也很前言，winQSB2.0对于普通甚至深入研究运输问题就已经是简单而又使用、耐用、好用的了。现在相关的杂志、期刊都越来越多关于管理运筹学，关于运输问题的文章论文初版，越来越得到重视。二、文献回顾随着物流行业和企业对物流运输要求的不断提高，企业的面临着更大的市场竞争，其运输活动在企业不断发展过程中，面临着越来越大难度的运输组合的选择决策问题。如何正确解决这个问题，是企业能够持续经营和发展不可忽视和必须面对的。这个问题同时也引起了企业界、学术界等社会各界的广泛关注。运输问题的实质是企业与运输组合的经济性问题，成功的企业通常都会面临如何选取最佳运输组合或运输路线这样一个重要问题，即以企业运输成本最小化作为确定最佳运输组合或运输路线的原落脚点。四、案例分析例：某公司下设生产同类产品的加工厂A1、A2、A3，生产的产品由4个销售点B1、B2、B3、B4出售。各工厂的生产量、各销售点的销量以及各工厂到各销售点的单位运价如下表：

Mosaicing of acoustic camera images

Mosaicing of acoustic camera images K.Kim,N.Neretti and N.Intrator Abstract:An algorithm for image registration and mosaicing on underwater sonar image sequences characterised by a high noise level,inhomogeneous illumination and low frame rate is presented.Imaging geometry of acoustic cameras is signi?cantly different from that of pinhole cameras.For a planar surface viewed through a pinhole camera undergoing translational and rotational motion,registration can be obtained via a projective transformation.For an acoustic camera,it is shown that,under the same conditions,an af?ne transformation is a good approximation.A novel image fusion method,which maximises the signal-to-noise ratio of the mosaic image is proposed.The full procedure includes illumination correction,feature based transformation estimation,and image fusion for mosaicing. 1Introduction The acquisition of underwater images is performed in noisy environments with low visibility.For optical images in those environments,often natural light is not available, and even if arti?cial light is applied,the visible range is limited. For this reason,sonar systems are widely used to obtain images of seabed or other underwater objects. An acoustic camera is a novel device that can produce a real time underwater image sequence.Detailed imaging methods of acoustic cameras can be found in[1].Acoustic cameras provide extremely high resolution(for a sonar)and rapid refresh rates[1].Despite those merits of acoustic cameras over other sonar systems,it still has shortcomings compared to normal optical cameras: (i)Limitation of sight range:Unlike optical cameras which have a2-D array of photosensors,acoustic cameras have a 1-D transducer array.2-D representation is obtained from the temporal sequence of the transducer array.For this reason,it can collect information from a limited range. (ii)Low signal-to-noise ratio(SNR):The size of the transducers is comparable to the wavelength of ultrasonic waves,so the intensity of a pixel depends not only on the amplitude,but also on the phase difference of the re?ected signal.This is the reason for the Rician distribution of the ultrasound image noise.In addition,there is often a background ultrasound noise in underwater environments. It follows that the SNR is signi?cantly lower than in optical images. (iii)Low resolution with respect to optical images:owing to the limitation in the transducer size,the number of transducers that can be packed in an array is physically restricted,and so is the number of pixels in the horizontal axis.For example,a mine reacquisition and identi?cation sonar(MIRIS)has64transducers[1].(iv)Inhomogeneous insoni?cation:The unique geometry of an acoustic camera requires the sonar device to be aligned parallel to the surface of interest,so that the whole surface falls within the vertical?eld of view of the acoustic camera [1].This alignment is not always trivial,and the misalign-ment often makes dark areas in acoustic camera images. The above limitations can be addressed by image mosai-cing,which is broadly used to build a wider view image [2–4],or to estimate the motion of a vehicle[5,6].For ordinary images,mosaicing is also used for image enhancement such as denoising,deblurring,or super-resolution[7,8]. There has been extensive research on image mosaicing, and its applications[9–13].However,standard methods for image registration[14,15]are not directly applicable to acoustic camera images,because of the discrepancy of image quality,inhomogeneous insoni?cation pro?le,and different geometry.Marks et al.have described a mosaicing algorithm of the ocean?oor taken with an optical camera [2].Rzhanov et al.have also described a mosaicing algorithm of underwater optical images resulting in high resolution seabed maps[3].Both of them deal with a similar problem of illumination,but use different methods:image matching by edge detection and Fourier based matching, which are not directly related to our work.In addition,since their mosaicing algorithms are not intended for image quality enhancement,we need to come up with a different mosaicing algorithm. In this paper,we describe a mosaicing algorithm for a sequence of acoustic camera images.We show that an af?ne transformation is appropriate for images taken from an acoustic camera undergoing translational and rotational motion.We propose a method to register acoustic camera images from a video sequence using a feature matching algorithm.Based on the parameters of image registration,a mosaic image is built.During the mosaicing,the image quality is enhanced in terms of SNR and resolution. 2Properties of acoustic camera images Sonar image acquisition includes several steps,insoni?ca-tion,scattering,and detection of the returning signal.In this Section,we describe physical aspects of images acquired from acoustic lens sonar systems,or acoustic cameras. q IEE,2005 IEE Proceedings online no.20045015 doi:10.1049/ip-rsn:20045015 The authors are with the Institute for Brain and Neural Systems,Brown University,Box1843Providence RI02912,USA E-mail:kio@https://www.360docs.net/doc/882058088.html, Paper?rst received21st May2004and in revised form22nd April2005

机器学习_CMU Face Images Data Set(CMU人脸图像数据集)

CMU Face Images Data Set(CMU人脸图像数据集) 数据摘要： This data consists of 640 black and white face images of people taken with varying pose (straight, left, right, up), expression (neutral, happy, sad, angry), eyes (wearing sunglasses or not), and size 中文关键词：人脸,图像,分类,UCI, 英文关键词： Faces,Image,Classification,UCI, 数据格式： TEXT 数据用途： This data set is used for classification. 数据详细介绍： CMU Face Images Data Set

Abstract: This data consists of 640 black and white face images of people taken with varying pose (straight, left, right, up), expression (neutral, happy, sad, angry), eyes (wearing sunglasses or not), and size Source: Original Owner and Donor: Tom Mitchell School of Computer Science Carnegie Mellon University tom.mitchell '@' https://www.360docs.net/doc/882058088.html, https://www.360docs.net/doc/882058088.html,/~tom/ Data Set Information: Each image can be characterized by the pose, expression, eyes, and size. There are 32 images for each person capturing every combination of features. To view the images, you can use the program xv. The image data can be found in /faces. This directory contains 20 subdirectories, one for each person, named by userid. Each of these directories contains several different face images of the same person. You will be interested in the images with the following naming convention: .pgm is the user id of the person in the image, and this field has 20 values: an2i, at33, boland, bpm, ch4f, cheyer, choon, danieln, glickman, karyadi, kawamura, kk49, megak, mitchell, night, phoebe, saavik, steffi, sz24, and tammo. is the head position of the person, and this field has 4 values: straight, left, right, up. is the facial expression of the person, and this field has 4 values:

winqsb使用方法

实验一WinQSB的基本操作一、实验目的了解WinQSB软件基本构成、运行界面和基本操作方法，使学生能基本掌握WinQSB 软件常用命令和功能。了解WinQSB软件在Windows环境下的文件管理操作。二、实验平台和环境 WinQSB是QSB的Windows版本，可以在Windows9X/ME/NT/2000/XP平台下运行。WinQSB V1.0共有19个子系统，分别用于解决运筹学不同方面的问题，详见表１-１。表1-1

三、实验内容和要求１.学会WinQSB的安装和启动方法２.熟悉WinQSB的界面和各项基本操作３.能用WinQSB软件与office文档交换数据。四、实验操作步骤 1.4.1安装 WinQSB的安装比较简单。双击Setup.exe，弹出窗口如图1-1所示：图1-1 输入要安装到哪个目录，点Continue按钮，弹出窗口如图1-2所示：

图1-2 输入用户名和公司或组织名称，点Continue按钮进行文件的复制，完成后弹出窗口如图1-3：图1-3 显示安装完成，点“确定”退出。 WinQSB软件安装完毕后，会在开始→程序→WinQSB中生成１９个菜单项，分别对应运筹学的１９个问题。如图1-4所示：

图1-4 具体功能见表1-1。针对不同的问题，选择不同的子菜单项，运行相应的程序，然后使用File菜单下的New Problem菜单来输入所需数据。 1.4.2运行 WinQSB基本上有三种窗口：启动窗口、数据输入窗口、结果输出窗口。现以Linear and Integer Programming为例加以说明：１.启动窗口。在开始菜单中选择Linear and Integer Programming，运行后出现启动窗口如下图1-5所示：图1-5 （１）标题栏：显示了程序的名称。（２）菜单栏：共有两个菜单：File和Help。 File菜单只有三个子菜单：New Problem、Load Problem和Exit。 New Problem：创建新问题 Load Problem：装载问题 Exit：退出

图像处理_Columbia University Image Library(COIL-100)(哥伦比亚大学图像数据库(COIL-100))

Columbia University Image Library(COIL-100)(哥伦比亚大学图像数据库(COIL-100)) 数据摘要： To database is available in two versions. The first, [unprocessed], consists of the original images that contain both the object and the background . In the second one, [processed], the background has been discarded, and the images consists of the smallest square that contains the object. For formal documentation look at the corresponding compressed technical report 中文关键词：几何,反射,姿态,实时,识别, 英文关键词： geometric,reflectance,pose,real-time,recognition, 数据格式： IMAGE 数据用途： For recognition 100 object in a real time

数据详细介绍： Columbia University Image Library (COIL-100) Access Instructions To download the 100 object database click at: [unprocessed]. For formal documentation look at the corresponding compressed technical report, [gzipped]. "Columbia Object Image Library (COIL-100)," S. A. Nene, S. K. Nayar and H. Murase, Technical Report CUCS-006-96, February 1996. [gzipped][uncompressed] 数据预览：

图片存储到image类型字段中

把D:\pic.jpg放到tempdb数据库Images表中 Images表结构程序截图——显示图片创建winform窗体，添加控件：一个PictureBox、两个Button 添加图片按钮的单击事件，代码如下： private void button1_Click(object sender, EventArgs e) { SqlConnection conn = new SqlConnection(connString); string sql = "insert into Images(Photo) values(@Photo)"; SqlCommand command = new SqlCommand(sql, conn); string picPath = @"D:\pic.jpg"; //图a?片?的ì?绝?对?路?¤径? try { FileStream fs = new FileStream(picPath, FileMode.Open, FileAccess.Read); Byte[] myByte = new Byte[fs.Length]; fs.Read(myByte, 0, myByte.Length);

fs.Close(); //转áa换?成¨|二t进?制?数oy据Y，ê?并?é保à?ê存??到ì?数oy据Y库a SqlParameter sqlPrm = new SqlParameter("@Photo", SqlDbType.VarBinary, myByte.Length, ParameterDirection.Input, false, 0, 0,null, DataRowVersion.Current, myByte); command.Parameters.Add(sqlPrm); conn.Open(); int count = command.ExecuteNonQuery(); if (count == 1) { MessageBox.Show("图a?片?添?¨a加¨?成¨|功|！ê?"); } else { MessageBox.Show("图a?片?添?¨a加¨?失o?ì败?¨1！ê?"); } } catch (Exception ex) { MessageBox.Show(ex.Message); } finally { conn.Close(); } } 显示图片按钮的单击事件，代码如下： private void button2_Click(object sender, EventArgs e) { SqlConnection conn = new SqlConnection(connString); string sql = "select * from Images"; try { conn.Open(); SqlCommand command = new SqlCommand(sql, conn); SqlDataAdapter dataAdapter = new SqlDataAdapter(command); DataSet dataSet = new DataSet(); dataAdapter.Fill(dataSet, "Images"); int count = dataSet.Tables["Images"].Rows.Count; if (count > 0) { Byte[] myByte = new byte[0]; myByte = (Byte[])(dataSet.Tables["Images"].Rows[count - 1]["Photo"]); MemoryStream ms = new MemoryStream(myByte); pictureBox1.Image = Image.FromStream(ms);