computer vision book

Install cross-platform computer vision library OpenCV in CentOS 6.5 Opencv is a cross-platform computer vision library that can be used for image processing. The following uses Opencv2.3.1 as an example. If you do not know how to install it, you can check it out. Opencv is a cross-platform

Accelerating computer vision algorithms using opencl on the mobile GPU March 12th, 2013 Abstract: Recently, general-purpose computing on graphics processing units (gpgpu) has been enabled on mobile devices thanks to the emerging heterogeneous programming models such as opencl. the capability of gpgpu on mobile devices opens a new era for mobile computing and can enable computationally demaning

De-mystifying Good and good papers by Fei-fei Li, 2009.03.01 Please remember this: 1000+ Computer Vision papers get published every Only 5-10 are worth reading and remembering! Since Many of your are writing your papers now, I thought the I ' d share these thoughts and you. I probably have said all of these in various points during our group and individual meetings. But as I continue my AC reviews This is

Computer vision is to make the computer understand the image and video, the purpose of this series of blog is to deepen their learning computer vision in the process of understanding and review of relevant knowledge. Many of the contents refer to: Textbook "Computervision:al

Computer Vision Conference Class A Iccv:international Conference on Computer vision cvpr:international Conference on computer vision and Pattern Recognitio n Class B eccv:european Conference on

Mahotas is a Python library for computer vision and image processing. It contains a large number of image processing algorithms, C + + implementation form, improve performance. A completely numpy-based array, as its data type, has a very clean Python algorithm interface.Include algorithm Watershed. Convex point calculation. Hit/hit, thinning algorithm. Zenit haralick, Lycium barbarum po

From: http://www.cvchina.info/2011/04/27/mea/ Transferred from Lao Yang's blogAnd focus on the physical and mental health of mobile computing, computer vision, 3C digital, IT web, and Lao Yang. I heard that the new name is meal snap.YesIPhone that calculates the calories of food in photosProgramTo count the total daily calorie intake of users and monitor the health of the diet. This idea is good,

left is the original, and the X-side wizard image on the rightBelow: The left is the Y-side wizard number image, the right image is the gradient imageIt can be seen that the Prewitt operator can detect the edge of the image, but the detection result is coarser and has a lot of noise. Sobel operator of approximate derivative Sobel operators are similar to Prewitt, but they are better than Prewitt operators.The Sobel operator in the x direction isThe Sobel operator in the y direction isThe

In the previous article, we explained the edge gradient computing function. This article describes the image pyramid. Image pyramid is widely used in computer vision applications. Image pyramid is an image set, all the images in the set are derived from the same original image and obtained through continuous downsampling of the original image. Preface In the previous article, we explained the edge gradient

Recommendations for "Computer vision" conference submissionsA call for paper website, small recommended to me: http://www.wikicfp.com/cfp/You can add your own attention to the meeting, will generate the corresponding deadline list, very much ~The other is the CCF recommended rankings of CAS: http://www.ccf.org.cn/sites/ccf/paiming.jsp, which lists the relevant periodical meetings.(reprint please indicate au

This article summarizes the image storage format that I understand.The data in the computer is binary, so the picture is no exception.This is a description of the OpenCV document, which is stored in the code using a matrix.Similar is (BGR format):The smallest unit of the picture is the pixel, here is the BGR (usually the notation of blud, Green, and red) that represents each pixel corresponding to the value (here BGR the mixture, can get all the value

Because the current plan is familiar with the language and library, and the image feature extraction theory is very boring, and it is likely to be inefficient, so the computer Vision feature extraction This Part skipped, direct start and deep learning with a closer target detection recognition part.This section describes the functions that extract the corner features of an image in OpenCV3:1# coding=utf-82

ObjectiveIn the field of computer vision CV, visual tracking is one of the important sub-problems. From my point of view, visual tracking is used on robots, on mobile devices, so why not put some tracking algorithms on the iphone to see the actual tracking effect. This is the most realistic comparison, the use of some video is not practical, and the key is not very good comparison of real-time. For mobile d

EMCV: OpenCV that can be run on the DSP EMCV Project Home: HTTP://SF.NET/PROJECTS/EMCVEMCV all called embedded computer Vision Library, is aComputer Vision Library running on the DM64X series DSP. EMCV provides a fully consistent function interface with OPENCV, and with EMCV, you can easily port your OPENCV algorithm to a DSP without even changing one line of co

1. First, we also press the Win7 flagship computer keyboard Win+r shortcut to open the computer's running window, in the open running window, we enter CMD and click Enter, so that we can open the Win7 flagship version of the Computer Command Prompt window. 2. Again open the Command Prompt window, let's enter the command code directly: @reg Delete hkey_classes_rootdirectorybackgroundshellexcontextmen

))#generation of 5*5 Gaussian operators with standard deviation of 2Suanzi = Np.fromfunction (func, (5,5), sigma=2)#Open the image and turn it into a grayscale imageImage = Image.open ("pika.jpg"). CONVERT ("L") Image_array=Np.array (image)#convolution of images and Gaussian operatorsImage2 = Signal.convolve2d (image_array,suanzi,mode="same")#results converted to 0-255Image2 = (Image2/float (Image2.max ())) *255#Display ImagePlt.subplot (2,1,1) plt.imshow (Image_array,cmap=Cm.gray) Plt.axis ("of

less than the given threshold)(3) Reset the size of the search window s and calculate the output parameters of the tracking target, and initialize the next frame mean shift search window with a new window sizeCamshift_2Represents an image in which a human face may be present in a video frame image when the face is tracked by the camshift algorithm. The black pixel has the lowest probability value, the white pixel probability is the highest, and the gray pixels are between them.(4) Jump to the s

Pose (Computer Vision) from Wikipedia, the free encyclopediajump: Navigation, Search InComputer Vision and inRobotics, a typical task is to identify specific objects in an image and to determine each object's position and orientation relative to some coordinate system. this information can be then be used, for example, to allow a robot to manipulate an object orT

From: http://www.bfcat.com /? Page_id = 268 this page will be updated occasionally, with as many computer vision databases and program resources as possible. Since the program summarized by uiuc Jia-bin Huang has been very comprehensive, I will not post it unless it is particularly recommended. Latest Update: 2013.03.26 Temple UniversitySome data and programs summarized by Haibin Ling Database Saliency D

UIUC's Jia-bin Huang students collected a lot of computer visual aspects of the code, links are as follows: https://netfiles.uiuc.edu/jbhuang1/www/resources/vision/index.html Type Topic Name Reference Link Code Structure from Motion Libmv http://code.google.com/p/libmv/