Do you often use a desktop computer and your notebook side-by-side? Do you hate switching the keyboard and mouse only for quickly replying to an email on the notebook, or for quickly checking a logfile on the desktop computer?

There is a free and easy solution to the problem on Linux and Mac: Use Synergy. It is a small and effective TCP/IP-based client-server application that lets you share keyboard and mouse of one machine with another one, with slide transition of the control via mouse movement just as with multiple screens in cinerama mode. This is much more handy than using a KVM-switch, as it doesn't require to switch off the screen of the other computer, and even allows for sharing the clipboard!

A short and good tutorial is available at a March 2009 article on LinuxMag.

Due to growing requests, I just put an old D.I.Y. tutorial on opening an Acer Travelmate 613 back online. The tutorial can be found here. It is written in German, but has several photos in it.

Anyway, please note before following the tutorial: I opened such a device many years ago for disconnecting the internal battery, after the notebook suddenly had a bios password enabled. While it helped resetting the bios password, it didn't solve the problem ultimately: The TM 613 had a security chipcard reader which was also randomly enabled and naturally didn't respond to the empty factory cards I had. So I ended up sending the device to the Acer people, who fixed the problem fast and for free.

I was looking for an easy way to derive a projection matrix corresponding to the camera of images rendered with blender. Given such a 3×4 projection matrix P, I want to define a 3D point in the blender scene, multiply it with the matrix and paint it into the existing image. For example, using Matlab to draw the scene origin as a red plus sign onto the image, I want to write


imshow('blender_img.jpg');
hold on;
X = [0 0 0 1]';
x = P*X;
x = x(1:2)/x(3);
plot(x(1),x(2),'r+');
hold off;


Deriving P turns out to be not documented at all, and besides knowledge on the computer graphics pipelines requires some trial and error. Today I managed to solve the problem, so here's the solution.

First of all, collect the camera position and orientation from the "Transform Properties" dialog, as shown in the image above. In Matlab you get the translation vector and rotation matrix via


X0 = [2 -10 4]';
o = 70*pi/180;
p = 15*pi/180;
k = -10*pi/180;
Ro=[1 0 0; 0 cos(o) -sin(o); 0 sin(o) cos(o)];
Rp=[cos(p) 0 sin(p); 0 1 0; -sin(p) 0 cos(p)];
Rk=[cos(k) -sin(k) 0; sin(k) cos(k) 0; 0 0 1];
R = Rk*Rp*Ro;


Now we need to derive the calibration matrix. Unfortunately, the focal length value in blender is neither documented nor standard. However, it is possible to display the lens angle alpha in degrees, referring to the wider image dimension, as shown in the image below. In the example we have alpha=49.13.

From the image resolution, which is here assumed to be 800×600, we get the focal length in pixel from fl=-400/(49.13*pi/180/2). Observe the minus!

The final projection matrix P is obtained in Matlab using


fl = -400/(49.13*pi/180/2);
K = [fl 0 400; 0 fl 300; 0 0 1];
P = K*diag([1 -1 1])*R'*[eye(3) -X0];


Note the flipping of the y axis which results in a left handed system. A
student is planning to write an export script for blender to write
P to file, which I'll post here.

I just discovered eigen, a really nice template library for linear algebra. I was using newmat until now, but was not very satisfied with its API design, and was looking for a single efficient library for both small (3×3) and large matrices. That is were eigen comes in: It has a very intuitive and handy API and can handle both fixed and dynamic-sized matrices in a unified way. Some highlights are

• Direct mapping of STL vector and C array memory into eigen's classes
• Classes for transformations, including quaternions (!)
• Sparse matrix support
• Handy typedefs for common structures, i.e. Vector3f for a 3-float-vector and Matrix2d for a 2×2-double matrix
• Comma initialization aka Vector3f X = Vector3f::Zero(); X << 1, 2, 3;

Eigen is a pure template library, meaning that you can include it in your project by copying the 1-2 MB of Header files into your source tree.

Really great work!

An extension of our 2009 BMVC paper has been accepted for publication in the International Journal of Computer Vision. Besides a more detailed evaluation on the completenss of combinations of local feature detectors, it covers the theory for a new sparse keypoint detector based on the maximum entropy principle. The print version of the paper will appear in summer 2010.

You can use the Java Native Interface to call native code written in C++ directly from Java - and vice versa, which is less often used. When calling Java from C/C++, a virtual machine has to be launched before calling classes, using the so-called "Invocation Interface". A simple example can be found here.

It is important that you do not use underscores in the Java class names when implementing this scenario - JNI won't find your classes then, as happened to me using Sun's Java 6 JRE. Unnecessary to mention that it took Thomas and me about on hour to find the problem...