Back for download: Tutorial on opening an Acer Travelmate 613
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.
How to convert Blender camera settings into a projection matrix
I was looking for an easy way to derive a projection matrix corresponding to
the camera of images rendered with blender. Given
such a 3x4 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 800x600, 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/tan(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];
Thanks to Daniel Berjon at Disney Research for pointing me to the tangens that
was missing in the above code snippet. 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.
Eigen: A convenient and fast C++ template library for linear algebra
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 (3x3) 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.
Vector3ffor a 3-float-vector andMatrix2dfor a 2x2-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!