So, it's a little different than what I have on my Mac, so it looks a little different.

But let's summarize.

What did we see yesterday?

No mind map today.

Today, we finalized the chapter on light fields and the idea how to generate images from artificial

images from a sequence of given images.

And I have a few videos with me.

Hopefully this works on this machine here.

So this is, for instance, an example of an input sequence.

You see that's a real world scene.

You see the liver, you see the gall bladder, you see also the others, nice things in the

human body.

Hold on a second.

No.

That's not what I wanted to show right now.

And what we do is, we compute out of this the 3D surface and the camera motion.

And what you see here is these are the focal points of the camera.

So that's the way I moved the endoscope.

And I don't know how to run the finite, infinite loop here.

And here you see the surface point.

You see the Rucola can here.

You see the surface of the liver.

And these points were computed using structure from motion approaches.

So the camera motion you see above here.

And the surface points, they were computed using the factorization methods we have discussed

several hours ago.

And this is the input for the light field reconstruction.

Here again the input scene.

So these are the images.

Where is now my film?

The images and the 3D information is used to generate sequences like that here.

And this is now an example where we have a rendered image using light fields.

And this is registered with a CT data set where you see for instance the vessels.

You can now embed the vessels of the CT data set into the artificial views generated by

a light field such that the surgeon gets for instance much more information.

You know where under the surface are the vessels and so on.

So it's called augmented reality, what we are doing here.

Augmented reality.

And we do not do that much augmented reality in our lab.

My colleague in Munich, Professor Navapi, has a chair for, or a whole lab for, augmented

reality in medicine.

So they are doing much more than actually we do.

And they work on techniques how we can, you know, augment the CTOS for instance, the surgery

field with additional information such that the surgeon can do much more and see much

more than he can do today.

Then we talked about, before that we talked about magnetic navigation.

And here is one video I also find somewhat impressive.

You see here how the catheter tip is moved around using the magnetic field.

And you can do tremendous movements with a magnetic field that you can't do actually

if you use all the mechanical steering devices that catheters today provide.