That makes alot of sense, thanks for the additional info!

So is it kind of like performing a convolution from the sets of pixels from one image onto the other image and finding the closest match from that?

+Jan Dvořák Well, there _are_ extra bits. Don't know if they contain what you wanted to see but I wanted to make sure you checked.

+Jan Dvořák Watch it backwards?

+hoopshank lololol awesome response

whereas your comment started where I hoped it would end.

+DeJayHank Google "disparity map" and look at the image results, you'll see a bunch of examples of what that might look like.

+Kruglord Well I know what it looks like because I've been working with Stereo matching algorithms with and without OpenCV, but I thought it would have been a good addition in the video for people who haven't seen.

+Kruglord Don't forget MSER, these are especially useful (area) features for wide-baseline stereo. Feature detectors and descriptors alone are an interesting topic.

+steve1978ger That's why stereo vision is no longer used in most cases, the current laser and RGBD cameras are easier and more effective in depth feature recognition.

....'like even rather a simple animal' - only predators have binocular vision which in turn are the most advanced biological life on this planet, like humans. overlapping field of vision might appear in some avians, but because totally different reasons (flight) and only for a few degrees, unlike predators who have true stereoscopic vision, there is no simple animal with that kind of trait

@@gigige5928 - okay, very simple animals may not have binocular vision, but "only predators" is an overgeneralization.

+peterjamesfinn The video glosses over this fact (for good reason) but the camera calibration step they mentioned is actually a very important and relatively complex step in the whole system. Because the relative position of the two cameras determines the measurement of the rest of the system, even very small errors in their estimated position can have huge impacts on the precision of everything else. For this reason, in stereo-vision systems the cameras tend to be rigidly mounted together, and their position determined in a separate step before they're used in any other measurements. Now, it's common to have a system that only has a single camera, that takes lots of pictures and moves around the scene alone rather than having a pair. This method relies on a simultaneous calculation of the camera's position at each photo location, and the location of the features in each photo. This can be fairly accurate as well, but it also has it's limitations. Specifically, the scale is indeterminate without additional observations, so you can only record the shape of the scene, not the size. Also, as mentioned in the video, the camera's locations can only be determined through features common to different images, which leads us into the correspondence problem. There are methods available to solve this problem, but they're complex and take a lot of time to calculate, even with today's powerful computers.

+Hayden Muscat Yeah there is a lot more going on in the brain for distance estimation, like just knowing what size cars usually are or a mug or whatever is enough to decently judge its distance from you even with a single image. There are algorithms that judge depth by taking several pictures from one camera with different focus for every image. This wouldn't quite work on moving objects though since it takes time to get enough pictures for it to be useful.

+Ted Chirvasiu Yeah I'd like to know too

Dota 2 when the clock hits night time.

+Ancient Apparition I also heard it in Dofus, WoW and HoTS

+WiWiPiWiWi Essentially you're using one eye to gather information that you'd normally get with two eyes

+WiWiPiWiWi That would work with a camera as well, but only if the object(s) you are taking pictures of is stationary during the whole process, and you know how far you moved the camera.

+GISP Subaru have a system (called 'EyeSight' strangely enough) that uses 'stereo' cameras mounted high in the windscreen to detect obstacles and warn the driver if they get too close, applying the brakes if necessary.

No need for gps, wifi/bluetooth triangulation could do it more precisely. Of course we would need 3 or more phones.

+Purple Blaze Google(not sure of the project name, but it's to do with google earth/maps) and Microsoft(Photo Tourism) already do this using peoples images, then they build up a 3d map of an area using those individual images. I dont think that accuarate/any gps data is a requirement, I think the algorithms used are clever enough to extrapolate the position.

No.

I don't think so. For example if you use 3 cameras named a, b, c, you have to draw the triangles for a-b, b-c, a-c. It would be more accurate, but it would cost 3 times processing power.

+MrAlbedo39 You can't really determine the coordinate of a point that only appears in one image. All you can say is that it exists, it falls on the epi-polar line outside of the bounds of the second image. So is either too close or too far to be seen by both cameras.

+Kruglord I'm more interested in how that occluded point ends up being represented in the 3-D result. Does it appear as a flaw that must be manually corrected?

+R.J. Reynolds Specularity (highly reflective surfaces) generally cause the correspondence to break down, resulting in what effectively appears to be occlusion in the depth map.

+Noah Williams It's a straight line between the camera and the object.

Elias Simon No I mean the one that the other camera has that can be quickly checked to see if it has the same value.

+Jake Surname You might have trouble for a while, but you'd adjust, because your pattern matching ability is still much better than a computer's.

+Jake Surname since you won't wake up one morning with your eye-distance being completely different, it doesn't matter. even if you grow a little, the changes are so small, that you can easily adapt. If you woke up and your vision was impaired by

You can simulate moving your eyes with a series of mirrors. Take one of those toy periscopes, and turn it sideways. Now your eyes are suddenly very far apart.

+R3Testa Suddenly, superhuman depth perception :)

+MMMIK13 Accuracy, lack of colour information, limited depth... At my work we use tens of fixed IR cameras to do motion capture, there is no way it could be reasonably done with ultrasound.

***** Hmm, but in the example at the beginning he talked about using Stereo 3D Vision as an alternative to lasers, and in that case, do you think ultrasound would work better?

Or radar. Google's project soli is doing exactly this. Pretty interesting

+Syukri Lajin Radar uses ultrasound dunnit, isn't that what the previous guy was referring to?

Akașșș ultrasound uses.. sound. radar uses electromagnetic waves. if i'm not wrong

Ye fock'n non brit :D

+Jimi Leander I'm Canadian eh. The Queen is on my money. Pretty British if you ask me.

+Marcel Robitaille He's close to having a speech impediment, (e.g. notice "ovver"). It may be an English public (expensive private) school accent/affectation.

+avro549B "Peasant accent" :D

in what way?

+j7ndominica0 i see two cube popping towards me diagonal to each other and a square and a circle with a circle inside popping in

"gooder"

+joelproko Stereograms can be so cool, with detailed shapes and customized backgrounds, and the example they go with are some simple shapes over static...

i was expecting more nerdy stuff :(

+realcygnus ??? but the math there is really secondary to the principal core of the mechanism ie: how to simplify the problem to make solving it actually feasible instead of matching pixel by pixel on the entire image

+realcygnus The maths tends to use a lot of linear algebra, which is probably beyond the scope of these videos.

You do realize saying something doesnt make it true.

I Am The Way You do realize you are communicating with me on a device that can show if I am right or wrong. I am sorry if I do not cite my work in the KZfaq comment section.