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Showing posts from November, 2015

Computer vision and social media brands analysis

Computer vision and brands taging This year, I have conducted a number of meetings with many people about same and same topics. Idea is simple but what about solution and realization. Is it simple to?  Let me comment or message pls.  What is going on? Brand recognition, automatic tags and statistics from the users picture.  If you know some kind of service like this pls let me know. I really want to discuss limitation and realization of these kind of projects.  We are all working on image segmentation and scene understanding using random trees, forest, ferns and deep learning methods. We are trying to find horses in images and tennis racket. . . . etc. I am really glad that, I am mainly working with detection up to 10 category. What about analysis and recognition of brands like on picture. And worse, Imagine case of analyze Instagram images and your output look like this. user: Vladimir, where: noLocated, brands: 2 [starbucks coffee, juice]  In advance th

Helicopter with vibrating suspended load

Position and vibration control This is really nice control example on experimental tool developed in our group at Czech Technical University in Prague. The experiment on video deal with  oscillation  of suspended load during helicopter  maneuver . The goal is control the Helicopter position with standard control loops which are conventional in real cases. The second important goal is control vibration of suspended load.  Signal Shaper  In this examples is part of our research publicated in such prestigious journals[1] [2]. [1]Vyhlidal T., Hromcik M., Kucera V. Anderle M., On feedback architectures with zero vibration signal, Accepted IEEE Transaction on Automatic Control as regular paper [2]Vyhlidal T., Kucera V., Hromcik M, Signal shapers with distribute delays: spectral analysis and design,  Automatica, Vol 49, Issue 11, November 2013, pp 3484-3489

Basic Face Detection, Opencv 3 Visual Studio 2015

Basic Opencv Face Detection Tutorial Basic Opencv C++ tutorial how to detect the face from video image and any source you can achieve. If you have little bit skills with programing you can just achieve the result under 10 minutes. I would like to reccomend also the installation by NUGET package. It is the fastest approach in Visual Studio how to start coding with opencv..  Problem with CascadeClassifier detectMultiScale Opencv 3.0.0. Windows prebuild libs Problem is that in many cases with 32 bit Opencv 3.0.0 Windows version in debug and in release mode. I thing any of haarcascade_xxx return vector<Rect> Faces (testing number of cascades is 7). The length of the vector is incomprehensibly bigger than I can expect with my parameters and experiences with previous Opencv version.. vector<Rect> of detection is to big  This is some kind of bug that I try to find in opencv source. What is surprising is fact that 64 bit version of Opencv works fine in my case. 

Install opencv Visual Studio 2015

Install opencv for Visual Studio 2015  Opencv tutorial how to build opencv from source in Visual Studio 2015. This is usefull when the new version just release and there is no prebuild library awailable..  If you download prebuild libs for windows Visual studio some times agou there is problem the newest VS just mussing. Lets checkt the version of libraries and VS. Prebuild libs are only for version VC11 and VC12. This mean Visual Studio 2012 and 2013. This step helps you compile your own opencv libs for VC14  - Visual Studio 2015 Community edition. Important !!  Now a days just use NUGET packages in Visual studio and you can code under 1 minutes. here . Prepare third party libs for opencv  This step depends on your requirements. If you want python lets install python. But i can reccomend to install following parts.  Intel © Threading Building Blocks ( TBB ) Intel © Integrated Performance Primitives ( IPP ) Build opencv 3.0.0  Downloa

Kalman Filter simple tracking example.

This is simple tracking example of moving object.  Basic concept is simple as following steps  Use background subtraction    Code Here Draw Rectangle over object  (blue) (Use coordinates of center (X,Y)) Init Kalman filter (red object) with detected (X,Y) coordinates If measured position of the object is available update kalman filter.  If measured position is not available just read predicated state of kalam filter

Opencv VideoCapture File, Web Camera, RTSP stream

Opencv VideoCapture File, Camera and stream Opencv tutorial simple code in C++ to capture video from File, Ip camera stream and also the web camera plug into the computer. The key is to have installed the FFMPEG especially in case of reading the stream of IP cameras. In windows just use Opencv Installation by Nugets packages  Here . Simple easy under 2 minutes installation. In Linux you need to follow the instruction below. If you are on Debian Like package system. Under Fedora Red hat dist just use a different approach. Code is simple and installation is the key..  Windows use nugets packages Linux you have to install and build Opencv With FFMPEG. Also simple.  It is easy to capture video in OpenCV Video capture  in OpenCV is a really easy task, but for a little bit experienced user.  What is the problem? The problem is the installation of Opencv without recommended dependencies. Just install all basic libs that are recommended on the website. # Basic packages

Martingate Betting roulette hell

About Martingate This really old betting strategy was popular in 18th century in France. Through the ages there are many modification and improvement to reduce risk. This strategy is still powerfull but you have to follow strict rulles to reduce risk to minimum. For humans it is the hardest thing to admit some losses and stop them before they lose so much money.    Betting strategy In basic this strategy is really simple.  Consider betting only on Red and Black numbers. Choose only one of them and bet your initial amount of the money.   Start betting with initial value 1$ to Red.  -If you win lets start again with initial value to same color.  -If you lose lets bet double at same color. 2$ -If you lose agail bet double than in previous round. 4$ In any case you win let start again with the initial value.  Imagine this series.  bet 1$ fail      -1$ bet 2$ fail      -3$ total bet 4$ fail      -7$ total  bet 8$ win      +1$ in total This is dangerous

Opencv C++ face detection Tutorial with Transparent image

Face detection and Transparent image in opencv  Face detection Opencv C++ tutorial about how to replace the face with mask. Easy steps to achieve results like many popular applications that just enhance your face. Code is just part that we already have available video reader written in opencv and just apply the face detection part with mask over the detected face.  Pixel by pixel color value filtering Let me explain how to add a transparent mask over the ROI in a video sequence.  This image of the anonymous mask has a white background. Add this image to the selected area  pixel by pixel with following condition. Add mask to the background video if the color of the mask is black. It s really simple idea. Image could be added over the roi in different way, but in the case you want to filter by pixel color value. This is example for you. Code Opencv Tutorial Just remember you need to at least figure out how to load the image or video into the IMG s

Opencv face detection and mask over the face

Opencv face detection and mask over the face Face detection is just the basic think you can do with the Opencv for fun. You can place the picture over the face. You can just replace by transparent mask like on video down here. Its easy and fun staff that you can achieved in 1 hour if you havent got any opencv skills, but you know somethink about the C++. Check the video example here and go to the tutorial :) Enjoy Codiang  Is there anyone who wants to know how to do it ? Tutorial is  Here