is the bunny hopping CXer the same fella or is this a fairly common skill?

Most people here can do that.

is the bunny hopping CXer the same fella or is this a fairly common skill?

Most people here think they can do that.

🙂

that ski jump thing Bimbler just posted – what view is that? I think I know what they’ve done ie corrected the image taken from a static headcam relative to the terrain but I’m not totally sure.

Good editing skills needed I’d imagine.

that ski jump thing Bimbler just posted – what view is that? I think I know what they’ve done ie corrected the image taken from a static headcam relative to the terrain but I’m not totally sure.

The original:

How the guy, from Reddit’s /r/ImageStabilization did it:

I used Hugin, which is based on PanoTools. Basically, I treat each frame of video as a different shot of a panorama. It’s way more tedious than using an automatic stabilizer, but you have enormous control over the final output.

Haha, thanks.
When everything works well, I just have to load in all the images, run one of the automatic control point detectors (this matches points on one image to another image), and then run the optimizer to solve for the camera angles and/or camera motion. I export remapped images which correct for the camera angles/motion, and make a GIF from those.
For something like this, I have to first manually identify where the horizontal lines are on one of the images and solve for the lens length (that’s the only way to correct for the fisheye lens this was filmed with).
The automatic control point detectors didn’t work because I only wanted to match very distant points like the mountains (I usually use either CPFind on short videos, as it tries to match each image to every other image, and AlignImageStack on long videos, which only matches each image to the image directly before and after it), so I did them by hand.
Then I solved only for “positions”, which is a misnomer since it solves for the camera orientation. Sometimes I also solve for translation when I also want to correct for camera movement, but I let the camera keep moving forward here. If there is zooming in and out, you can solve for that too. I got lucky here and didn’t have to worry about that.
Overall, it was a dumb idea even do this one, since it meant manually doing control point identification for 163 frames, but at least it’s had a good response. Most of them are much much easier.

In light of all the topical debate happening around the Winter Olympics

Winter Olympics

Surely:

Lizard fart 🙂

Where’s Bob?
Dunno, he was here a minute ago.

Whoops…

Oi, I used to work with the owner of one of those bottoms.
She will kick your head in…no really, she is hard as nails.

Jamie

Thanks for posting that – makes it sound both much easier and yet harder/more tedious than I thought. Very clever and that composite edit at the end is great.

She will kick your head in…no really, she is hard as nails.

But she has such a pretty smile

Beaming from cheek to cheek!

I hope this thread never dies….

Seems apt…

I still think that that era Impreza is definitely one of the best looking rally cars ever. Perfect proportions.

Jamie wins, again

[img]http://i.imgur.com/nSBYnig.gif[/img]