Laser Scanning

The idea is to project laser lines onto a flat surface, image them, and then put objects in front of the surface and compute the displacement made by the object.

Here is the flat base with a line on it:



Here is the line at the same position with objects intersecting:



Finding depth involves figuring out what the 2d projection of the normal line that is perpendicular to the wall at any point along the laser line. I'm working on this but it's also possible to guess an average line for low precision demonstration. The software looks for all points where it believes the laser is shining, and then computes the intersection of the normal line with the original object free laser line, and gets depth.

I had about 8 different images from laser lines, here are the results from two:





The yellow lines are the projected normals from the base line to the found laser line on the backpack and broom. There are some spurious results, and also on the dark woven backpack material the laser was not always reflected strongly enough to register.


The source code is here:

http://code.google.com/p/binarymillenium/source/browse/trunk/processing/laserscan

Multicamera Balloon Imagery

AHAB Tether Test from binarymillenium on Vimeo.

I originally was reminded of the unused source images because another team member recently posted some pictures from their camera, and then I made this, and then Bre posted about it, so it's getting a lot of positive feedback.

This video would have been made earlier but I had assumed that the cameras were screwy and firing at different times and image sequences would not line up at all- turns out they did, they just had wildly different start points.

Also I finished this school project that was kind of a simple occupancy grid inspired thing, this video shows parts of it:


2.5D from binarymillenium on Vimeo.

I might revisit some of this and get the registration code working (and working a lot faster), instead of cheating and using the known camera position and attitude.

Depth buffer to 3d coordinates?

I'm having trouble transforming screen coordinates back to 3d, which this post describes- can anyone help me?





---
Update - I've got it figured out now, I should have been using gluUnProject:



FloatBuffer fb;

fb = BufferUtil.newFloatBuffer(width*height);

gl.glReadPixels(0, 0, width, height, GL.GL_DEPTH_COMPONENT, GL.GL_FLOAT, fb);
fb.rewind();

int viewport[] = new int[4];
double[] proj=new double[16];
double[] model=new double[16];
gl.glGetIntegerv(GL.GL_VIEWPORT, viewport, 0);
gl.glGetDoublev(GL.GL_PROJECTION_MATRIX,proj,0);
gl.glGetDoublev(GL.GL_MODELVIEW_MATRIX,model,0);

...
for(int i...
for (int j...
...
glu.gluUnProject(i,height-j,rawd, model,0,proj,0,viewport,0,pos,0);
float d = (float)-pos[2];


After all that depth d will be linear and in proper world coordinates.

Artoolkit + rangefinder

Since my relatively inexpensive purely visual depth map approach wasn't that successful, I've tried it out using a rangefinder instead of a visible laser. This means I can point the video camera straight at the marker (which is attached to the rangefinder), and it can point at anything provided I don't tilt it so the camera can't see the marker/fiducial.

This is the result:


Artoolkit with a Rangefinder from binarymillenium on Vimeo.

The following plots show the tracked attitude of the rangefinder as measured by ARToolkit:






My left to right bottom to top scanning approach is very apparent.


And here is the tracked attitude (as a 3-component vector) plus the range vs. time:



You can see how cyclical it is, as I scan the floor in front of me the range doesn't change much until I reach one end and tilt the tripod up a little, and then later on I start to capture the two wheels of the car.

University of Washington BioRobotics Lab

I took a tour of the UW BioRobotics Lab, where an old professor of mine works on telerobotics with haptic interfaces.



This is a surgery robot called 'The Raven'. It's mostly camouflaged due to the large amounts of detail and contrast in the robot itself and in the background. The DV camera is going to be replaced by a pair of HD cameras that will provide stereo vision.



Multiple motors pull on cables seen in a later photo that control the manipulator end of the arm.










Blake Hannaford shows the arms that will replace the manually positioned arms seen in the previous photos.