No problem. This is a potentially confusing subject. Some of the more complex 3D methods can be tough to wrap your head around and require some complex visualization. This one is a lot simpler.
That's a valid question. There's more than one way to create 3D in machine vision. Chuck's upcoming February feature, already out in the print edition of DN, discusses this subject. The simplest, easiest, cheapest method is by using two 2D cameras in stereo, as does this QuantumVision product. This roughly emulates the stereoscopic vision of humans (and other primates), in that both of our eyes used together creates 3D stereo images. Others use more complex math and/or special image sensors, and/or special image processing.
Make sense. But forgive me if this is a silly question or perhaps I'm too immersed in 3D given my focus, but why do they call these cameras 3D if it's simply processing 2D data??
Basically, this is smaller than other stereo 3D cameras, and it's way smaller than other 2-camera 3D stereo cameras. Since it's a stereo 3D system, it's created with two 2D cameras, so there's really no new paradigm in that sense; you are still processing 2D data. You can process that data faster if you use the cameras independently. Another thing about this system is its rugged enclosure, which is why it's shown with water drops.
Ann, what's the use case for this type of system compared with a traditional 2D vision system or any of the stereo 3D systems? Am I saving money by going this route or is it purely a matter of increasing visibility without having to move to a totally new 3D paradigm?
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