Arne's profile - activity

This might happen, because you are running out of memory while compiling. Even though it works for the guy in the tutorial, that doesn't mean that the newer version of openCV you are using won't hit the magic point of exceeding the available memory. But you might try a newer version of your compiler or an older version of openCV. If that doesn't help you should consider cross-compiling it on your normal PC.

It seems that there isn't a function like imshow in the Java HighGUI package. But after a small search i found out that its possible to encode the image to a "BufferedImage" and then just load it into your GUI. So just load it like this:

Mat image_tmp = your image
MatOfByte matOfByte = new MatOfByte();

Highgui.imencode(".jpg", image_tmp, matOfByte); 

byte[] byteArray = matOfByte.toArray();
BufferedImage bufImage = null;

try {

    InputStream in = new ByteArrayInputStream(byteArray);
    bufImage = ImageIO.read(in);
} catch (Exception e) {
    e.printStackTrace();
}

and then draw it like that:

g.drawImage(bufImage , 0, 0, null);

g in this examples is an instance of the class Graphics

Hopefully this is what you were searching for.

I did change the row and column, otherwise the findCirclesGrid function won't find anything.

Hello, in my opinion. "learning" about the whole library in 45 days in detail is a little to ambitious. But there are a lot of examples out there for stuff like human detection. I think its possible to look at some of these and understand what is happening in these within 45 days. That its quite hard to learn about the whole library in less than two month is not about your skill its due the pure size of the library. I myself learned a lot from the OpenCV Cookbook which is available on Amazon and maybe eBay for little money. Furthermore the most helpful stuff in my opinion are the samples deployed with each OpenCV package. For your other question i would entrust the newest stable version to you, which is 2.4.6 at the moment. And you can use the programming language which you are most familiar with. There are just the normal limitations that java or python might be a bit slower due their run-time environment. But for trying yourself out in the beginning this shouldn't be a big problem. I hope my answers helped you a bit. Kind regards Arne

First i want to thank you for your quick answer. For testing i am using an extended version of the sample for stereo-calibration. I just recorded some images as advised in the ROS Wiki. And even if its not perfect i was able to make both sets look equal. (chessboard and circular marker) The strange thing is now, that even if not in all of the pictures the chessboard is found i will get a calibration. But when using the circular marker, the pattern in found in all images, i get NAN as rms and the rectified Image is gray. How is that possible while all patterns are found in almost the same poses as the chessboard, which is not found in all images. I am really confused.

Hello, i was evaluating different sets of parameters during the stereo-calibration. It turned out that only 25 calibrations with circular markers were under the top 1000 of about 6720 calibrations ordered by rms. Does this have anything to do with a lack of functions like cornersubpix for circular markers. Because according to some literature i read about photogrammetry, the circular markers should be much better to detect while having a better precision. I hope you can explain this issue to me, and tell me if i am right with my guess.

kind regards