Linaro + openCV

Well at the beginning of the blog some one, tell me to use ubuntu-linaro, wich is more focused to ARM processors

The Linaro use the library libjpeg-turbo directly and not is necessary to install as I do in Raspbian + opencv + libjpeg-turbo

The installation of Ubuntu-Linaro is quite simple, and can be downloaded from the berryboot, in the same way as I did with Raspbian.

Installing OpenCV

Well I find some troubles when I tried to install opencv in Linaro.

When I added the requisists to install openCV

sudo apt-get -y install build-essential cmake pkg-config libpng12-0 libpng12-dev libpng++-dev libpng3 libpnglite-dev zlib1g-dbg zlib1g zlib1g-dev pngtools libtiff4-dev libtiff4 libtiffxx0c2 libtiff-tools

sudo apt-get -y install libjpeg8 libjpeg8-dev libjpeg8-dbg libjpeg-progs ffmpeg libavcodec-dev libavcodec53 libavformat53 libavformat-dev libgstreamer0.10-0-dbg libgstreamer0.10-0 libgstreamer0.10-dev libxine1-ffmpeg libxine-dev libxine1-bin libunicap2 libunicap2-dev libdc1394-22-dev libdc1394-22 libdc1394-utils swig libv4l-0 libv4l-dev

I had to add this library, if not our programs will give us errors, but there are a lot of information in google to solve the problems.

sudo apt-get install libgtk2.0-dev 

cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D BUILD_EXAMPLES=ON ..

and after that continue the installation of openCV

It's any one there ?

Well there are a couple of possibilities to check if there are any object, person

But one of the simplest is to use Haar-like features.

To work with Haar features (see the example FaceDetect.cpp in your directory OpenCV-2.4.3/samples/c/facedetect.cpp)
But basically works with haar files which store an abstract of the information about what is a face (any object) and what is not a face (a object)

Depending of the necessity and the power of our machine, we should different haar libraries. Even we can build special libraries for our purposes. (but my i3 with 4 GB ram took 3 days to make one haar library about cars)

I used this three
  

"./haarcascades/haarcascade_frontalface_alt_tree.xml" (3.5 MB) (over 500ms)
"./haarcascades/haarcascade_frontalface_alt2.xml" (0.8 MB) (over 300 ms)
"./haarcascades/haarcascade_eye.xml" (0.4 MB) (over 200 ms)


Also depends the size of the image, I used the less quality (160x120) for the first ideas will works

The code is based in the sample, so you'll find the code there, any doubt ask me.

With this exercise I finish the first part of the project based on computer vision.
We can do a lot of things more, blobs, our haar libraries, structural analyzes, movement studies, etc... but all this exercise are outside of this scope.