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Using OpenCL causes application to hang at startup Hi, When building an application on Windows using OpenCV, the appli

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Thanks so much!

I had the same problem, run the below script from the build directory.

# !/usr/bin/python

import re
import os

def PatchFile(name):
    f = open(name, "r")
    lib_to_add = "-lv4l2"
    file_read = f.read()
    f.close()
    if lib_to_add in file_read:
        pass
    else:
        if "-lv4l1" in file_read:
          print "Appending to file " + name
          f = open(name, "w")
          new_contents = file_read + " -lv4l2"
          new_contents = new_contents.replace('\n', ' ').replace('\r', '')
          f.write(new_contents)
          f.close()

for root, dirs, files in os.walk(".", topdown=False):
    for name in files:
    file_name = os.path.join(root, name)
        if (name == "link.txt"):
        PatchFile(file_name)

I'd also like to know what is happening here?

I can't find the "initModule..." anywhere. Algorithm::getList() only shows 2 algorithms. What is going on?

It says in the performance section: http://www.apulus.com/performance/ that it uses openCV

I saw this on youtube: FlexCV and thought it looked pretty cool! Seems you can run a lot of OpenCV just by connecting blocks up live.

Looks interesting from the website

What do people think?

How do you calibrate a camera using known 3D points and their corresponding 2d image locations.

Using a chessboard is easy, is it the same method for real world points.

How then do you then get the cameras to output data in that coordinate system, so a point on the images gives the same 3D point via triangulation as was used in the calibration?

How do you stereo cameras so that the output of the triangulation is in a real world coordinate system, that is defined by known points?

OpenCV stereo calibration returns results based on the pose of the left hand camera being the reference coordinate system.

I am currently doing the following:

Intrinsically calibrating both the left and right camera using a chess board. This gives the Camera Matrix A, and the distortion coefficients for the camera.

Running stereo calibrate, again using the chessboard, for both cameras. This returns the extrinsic parameters, but they are relative to the cameras and not the coordinate system I would like to use.

How do I calibrate the cameras in such a way that known 3D point locations, with their corresponding 2D pixel locations in both images provides a method of extrinsically calibrating so the output of triangulation will be in my coordinate system?