How to Fake a UFO Landing
A flying saucer descends onto an open field and lands, kicking up dust all around it. If this happened in a remake of The Day the Earth Stood Still nobody would blink. But imagine that instead of a big beautiful image executed with the precision and care of a big-budget feature, what you're watching looks like it fell on the cutting-room floor of The Blair Witch Project. You're not seeing this in a comfortable screening room at your local cinema, where the picture is clean, sharp and bigger than life, but rather you're standing gathered around a booth at your local science-fiction convention. The guy playing the video isn't a producer. He isn't even an independent filmmaker. He's a guy who's genuinely convinced that this video can't be faked. If it were, he says, the seams would show, and whoever gave this to him really did record evidence of alien visitation that the government is covering up, and that by showing this publicly, he's taking a terrible risk. But, he feels he must expose the fraud that governments and aliens perpetrate on unsuspecting citizens!
This scenario may sound like it clawed its way out of the X-Files' wastebasket, but as VisualFX technology gets ever cheaper and more ubiquitous, faking a video like this becomes no problem. Of course, it takes a lot of expertise and dedication to get the colors, shadows and reflections to match convincingly. One would think that getting the movement to match as the camera person runs and zooms with a handheld shot would be the most difficult part of the equation. Once upon a time, this was true.
It used to be that the only way you could achieve the movement precision necessary to sell an effect like this was to put your camera on a motion control rig and have a computer record the movements in the field and then reproduce them exactly (though to a smaller scale) in the post house where the artificial elements (in our case, the flying saucer and the dust) were photographed. Aside from being very cumbersome and expensive, this approach sharply limited the kinds of shots that an FX artist could do to those that could be reproduced by an electric gimbal and a prime lens.
No longer. The late 1990s saw a great flowering of research and development into the area of computerized match moving—matching the movement of different visual elements so that they appeared to exist organically in the same scene. Putting the computer in the mix both at the match moving and at the compositing stage gives a lot more control and freedom than previously.
Human visual acuity isn't the best on the planet, but it is startlingly good. With a little practice, an ordinary fellow sitting in the audience for The Matrix can spot the grain mismatch in shots that were too hastily done. Our visual cortex does the differential calculus to tell us “this doesn't belong here”. It follows that this same mental apparatus could be employed to create the trickery in the first place. With most VisualFX work, there are complicated tools, and then there is doing it by hand. Like most other fields of human endeavor, the better an artist is, the fewer training wheels he or she generally will rely on. So, why not do match moving by hand?
The short answer is that many artists do, under some circumstances. Other times, there is an interaction between the artist and the match-moving software, with the artist choosing points for the software to track, either because the tool doesn't detect the right points, latches on to points that aren't appropriate or doesn't do point detection at all.
However, the art of motion tracking is nontrivial. Although our visual cortexes are excellent at detecting error, they are somewhat less excellent at projecting perfection outward. We do not create grand, realistic paintings naturally—indeed, we have to be taught to see light, shadow, form and so on in a certain way in order ponder even attempting to work like a Bouguereau or a Leonardo. Similarly, our ability actually to distinguish motion that doesn't fit is quite keen, although our ability to create a perfect motion path is coarse by comparison—something we don't notice until after we play it back and see the drift creeping in even with the most careful hand-tracks.
Of course, a match-moving program won't always get a perfect track, but the interaction of a good artist with a good program delivers top-notch results.
Aside from the fact that it's free, why use Voodoo for this project?
The truth is that Voodoo isn't going to solve every match-moving problem, even leaving out the ultra-delicate moves that the higher-end match movers handle better. The field of match moving is basically divided in two: 2-D motion tracking and 3-D camera tracking.
2-D motion tracking is the technology used in compositors to affix a new element to a specific point in the frame. A user generally will select one or two feature points, and the computer then will follow the points around the frame as the objects move within it. When the tracker slides off the selected point, the artist gently will correct it to keep the track from drifting. Two commonplace examples of this process can be seen in blurring suspects' faces on Cops! and in placing virtual advertisements on infield walls at baseball games. 2-D tracking tracks only the position of an object within the frame, which gives it a double-barreled Achilles' heel: parallax and perspective.
Parallax is the phenomenon whereby foreground objects seem to move faster than do background objects. As your point of view moves, the angle at which you perceive objects changes subtly, which is why you see a parallax driving down the road. With 2-D tracking, your track marks are pretty much all you get. This can be a problem if, for instance, you're moving over a greenscreen and the digital set is supposed to extend for quite a ways down in depth. As soon as you add depth to lateral movement, particularly when your track marks are close to the camera, you need to work in 3-D, or you have to fake parallax by hand—a dubious and difficult undertaking that easily shatters the illusion you're trying to create. A really good artist can pull it off, but it takes a lot of practice.
Perspective is the other wild card in the equation. Lenses do not see the world as it is. Instead, every lens distorts the world in certain mathematically predictable ways. This distortion is closely related to focal length and aperture, and measuring the distortion accurately is essential to tracking elements properly in the shot. This wild card gets even wilder with zoom (extending the lens to get a closer shot) and dolly-in (moving the camera toward a subject) movements, which involve constantly changing perspective in one fashion or another along the z axis, which is the axis that 2-D motion tracking can't cope with. Perspective changes also can be faked, but it's far more difficult than faking parallax and far more time consuming.
This is where 3-D camera tracking comes in. Instead of simply tracking the location of certain user-selected features to create a good 2-D track, the computer attempts to guess the position and motion of the camera based on the footage. Pitch, yaw, roll and lens length are all calculated based solely on the finished video (though any information you have and can input manually will make it work faster). The ability to reconstruct all these parameters accurately means that the problems of parallax and perspective are solved, even during dolly and zoom moves. Needless to say, this is a mathematically complex process designed to test the minds of even the most ardent effects artist who wasn't also a comp-sci or optics major at a university. Nonetheless, the algorithms for pulling this off are well known and included in most camera-tracking packages.
Although most 2-D motion trackers are built in to existing compositing systems (such as After Effects), 3-D camera trackers operate on a standalone basis and export their data—camera settings and movement, as well as the “point cloud”—to various 3-D programs, and it is in the 3-D program where the magic happens. The 3-D program also gives an extra measure of control and refinement beyond what the tracker itself allows, as you can tweak the camera animation curves.
I said earlier that the 1990s saw a lot of funding into creating software like this. Well, as every tech-junkie knows, where thy research funding is, there thy grad students also will be. Thanks to a team of particularly dedicated grad students in Hannover, Germany, the technology to match camera movement in three dimensions is available to Linux and Windows users for free—a very good deal, considering that comparable commercial packages run upward of several thousand dollars a seat. For the savings, you do sacrifice some sophistication in the ability to fine-tune your shot, but for most applications, Voodoo does very well.
So, grab a copy of it, and let's get you ready for your appearance on the Art Bell show, peddling your newest Genuine UFO Video (tm)!
|PostgreSQL, the NoSQL Database||Jan 29, 2015|
|HPC Cluster Grant Accepting Applications!||Jan 28, 2015|
|Sharing Admin Privileges for Many Hosts Securely||Jan 28, 2015|
|Red Hat Enterprise Linux 7.1 beta available on IBM Power Platform||Jan 23, 2015|
|Designing with Linux||Jan 22, 2015|
|Wondershaper—QOS in a Pinch||Jan 21, 2015|
- PostgreSQL, the NoSQL Database
- Sharing Admin Privileges for Many Hosts Securely
- HPC Cluster Grant Accepting Applications!
- Internet of Things Blows Away CES, and it May Be Hunting for YOU Next
- Ideal Backups with zbackup
- Wondershaper—QOS in a Pinch
- Designing with Linux
- Red Hat Enterprise Linux 7.1 beta available on IBM Power Platform
- Slow System? iotop Is Your Friend
- January 2015 Issue of Linux Journal: Security
Editorial Advisory Panel
Thank you to our 2014 Editorial Advisors!
- Jeff Parent
- Brad Baillio
- Nick Baronian
- Steve Case
- Chadalavada Kalyana
- Caleb Cullen
- Keir Davis
- Michael Eager
- Nick Faltys
- Dennis Frey
- Philip Jacob
- Jay Kruizenga
- Steve Marquez
- Dave McAllister
- Craig Oda
- Mike Roberts
- Chris Stark
- Patrick Swartz
- David Lynch
- Alicia Gibb
- Thomas Quinlan
- Carson McDonald
- Kristen Shoemaker
- Charnell Luchich
- James Walker
- Victor Gregorio
- Hari Boukis
- Brian Conner
- David Lane