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Emgu CV: OpenCV in .NET (C#, VB, C++ and more)

Emgu CV: OpenCV in .NET (C#, VB, C++ and more)

Crossfilter Fast Multidimensional Filtering for Coordinated Views Crossfilter is a JavaScript library for exploring large multivariate datasets in the browser. Crossfilter supports extremely fast (<30ms) interaction with coordinated views, even with datasets containing a million or more records; we built it to power analytics for Square Register, allowing merchants to slice and dice their payment history fluidly. Since most interactions only involve a single dimension, and then only small adjustments are made to the filter values, incremental filtering and reducing is significantly faster than starting from scratch. Crossfilter uses sorted indexes (and a few bit-twiddling hacks) to make this possible, dramatically increasing the perfor­mance of live histograms and top-K lists. For more details on how Crossfilter works, see the API reference. Example: Airline on-time performance February 28, 2001 236 mi. +139 min. 304 mi. +83 min. 569 mi. +172 min. 646 mi. +97 min. 370 mi. +73 min. 325 mi. +92 min. +16 min. 361 mi.

Camera Face Detection in C# Using Emgu CV (OpenCV in .NET) and WPF Download WPF Face Detection Solution File Hi there, this is a new tutorial category in my blog. It's Computer Vision. In this blog, I'd like to show you something cool. It's how to perform Face Detection using your camera / Webcam. You'll see how your application can detect faces from a captured image. This what you need to follow this tutorial: Microsoft Visual Studio 2010. After you've got what you need, it's time to rock! First thing you should do is installing Emgu CV. Next, let's open your Visual Studio and create a new WPF Project. Now, copy code below to make our user experience. Next, let's code it! using System; using System.Windows; using System.Windows.Controls; using System.Windows.Media.Imaging; using System.Windows.Threading; using Emgu.CV.Structure; using Emgu.CV; using System.Runtime.InteropServices; Initialize two objects Capture and HaarCascade. This last part is the routine. Here is the result of our work: Okay, I think that's all I can do in this post.

OpenTSDB - A Distributed, Scalable Monitoring System Evolution computations on C# Introduction There are many different research works done in the area of evolution computation, what caused a variety of different evolutional algorithms to appear. Many researchers studied these methods extensively and tried their application to the great range of tasks. It is a known fact, that there are many different problems exist, which impossible to solve precisely within a reasonable period of time using traditional methods. Also there are many problems, which do not have a formalized solution approach, what makes their solution very hard or even impossible using traditional methods. As an example is Traveling Salesman Problem (TSP), where it is required to find a shortest path around specified amount of cities, visiting all of them only once and returning back to the start city in the end. In this article, a C# library for evolution computation will be discussed. Evolution computations There are several selection operators exists [1 ]. Using the library Function Optimization

The R Project for Statistical Computing AForge.NET open source framework Introduction It so happened that from time to time during the past two years I was working on several research projects in the areas of Computer Vision and Artificial Intelligence. As a result of this work, a lot of code was produced and several articles on Code Project were published that describe some of these areas. Publishing these articles, I discovered that these areas are interesting not only to me, but to a wide range of developers as well. From the time of my first publication on Code Project, I received many different e-mails from many interesting people all over the world, who were applying some of my code to a great number of applications. The aim of this article is to make its publication to be an official opening of a new open source project AForge.NET - a C# framework for researchers in different areas of Computer Vision and Artificial Intelligence. Image processing Neural networks Evolution algorithms Image processing library Neural networks library Function optimization

Image Processing Lab in C# Introduction Image Processing Lab is a simple tool for image processing, which includes different filters and tools to analyze images available in the AForge.NET framework. It's easy to develop your own filters and to integrate them with the code or use the tools in your own application. You can create (save and load) your own convolution filters or filters based on standard mathematical morphology operators. A preview window allows you to view the results of changing filter parameters on the fly. A PhotoShop-like histogram allows you to get information about mean, standard deviation, median, minimum and maximum values. The program allows you to copy to or paste from clipboard, save and print images. Using the Code Most filters are designed to work with 24bpp RGB images or with grayscale images. System.Drawing.Bitmap image = (Bitmap) Bitmap.FromFile( fileName ); AForge.Imaging.Image.FormatImage( ref image ); It is easy to apply any filter to your image: HSL Filters Fourier Transformation

AForge.NET :: Computer Vision, Artificial Intelligence, Robotics Motion Detection Algorithms Introduction There are many approaches for motion detection in a continuous video stream. All of them are based on comparing of the current video frame with one from the previous frames or with something that we'll call background. In this article, I'll try to describe some of the most common approaches. In description of these algorithms I'll use the AForge.NET framework, which is described in some other articles on Code Project: [1], [2]. The demo application supports the following types of video sources: AVI files (using Video for Windows, interop library is included); updating JPEG from internet cameras; MJPEG (motion JPEG) streams from different internet cameras; local capture device (USB cameras or other capture devices, DirectShow interop library is included). Algorithms One of the most common approaches is to compare the current frame with the previous one. But most cameras produce a noisy image, so we'll get motion in such places, where there is no motion at all. Motion Alarm

CsGL - C# graphics library Use OpenGL in CSharp Application Download source - 151.99 KB Introduction This is a simple example about using OpenGL in CSharp application. The Workflow of Using OpenGL Create OpenGL with a specific area. Note: When we create the OpenGL, we don’t need any device handle. Do some initialization for OpenGL. Note: In fact, we draw the graphics to the DIB. public OpenGLBox() { InitializeComponent(); bool bRet = m_gl.Create(Width, Height); Debug.Assert(bRet == true); m_gl.ShadeModel(OpenGL.SMOOTH); m_gl.ClearColor(0.0f, 0.0f, 0.0f, 0.0f); m_gl.ClearDepth(1.0f); m_gl.Enable(OpenGL.DEPTH_TEST); m_gl.DepthFunc(OpenGL.LEQUAL); m_gl.Hint(OpenGL.PERSPECTIVE_CORRECTION_HINT, OpenGL.NICEST); } protected override void OnPaint(PaintEventArgs e) { m_gl.MakeCurrent(); if (OpenGLRender ! History This is the first version.

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