In order to get this bitmap represenation from the partial pattern I did the following in Photoshop:įirst I cropped the image to a rectangular region of spots, using perspective crop. All we have to do is to create a bitmap image with one pixel per pattern-point, white is a bright spot, black a dark spot. The fact of having an orthogonal grid with a more or less binary map of bright/dark spots simplifies the acquisition of the pattern. All spots are present, however only some spots are bright, the others are severely darkened. In the images you see quite clearly, that the pattern is made of spots in a regular orthogonal grid.
#Kinect random dot pattern iso
The camera was a Fuji Finepix F30 with long exposure (1/4s, ISO 3200) in macro mode, focal length 8mm (=36mm equiv.), mounted on a low-cost tripod and using the self-timer to not shake the camera when pressing the button. I used a fairly simple method: projecting the kinect-pattern on a wall in about 1 meter distance in a darkened room, and taking closeup photos of parts of the pattern from a distance of about 20 cm. Here is how I did it: Capturing the Images Therefore, I decided to create a map myself. Unfortunately, non of these approaches really mapped out the pattern. I will come back to these observations later. And in the center of these sub-patterns one point is much brighter than all the others. The rectangle seems to be tiled in 3×3 sub-patterns of different brightness. They show, that the pattern is basically rectangular but severely distorted into a pin cushion. futurepicture, nongenre, robot home, ros, anandtech or living place), tried to find some regularities in the pattern or made nice videos featuring the pattern. Searching the web, several people managed to capture the pattern in various qualities (e.g. And appart from the fact that it is projected by an infra-red laser diode and therefore invisible to the human eye, it should still be fairly easy to capture it with consumer cameras the Kinect does nothing else itself. Well, of course the pattern is in every kinect, and I strongly believe that it is the same pattern in each and every one of them, since it is a mass product. The first step in understanding the pattern is of course to get the pattern. On Prime Sense’s website’s FAQ they state that “The PrimeSensor™ technology is based on PrimeSense’s patent pending Light Coding™ technology”, which makes me speculate about some “code” in the pattern… Therefore, there must be something special about this projected pattern, that makes the computations especially simple. The fascinating part is, that kinect’s speckle pattern is constant over time, and that the depth-computations can be performed on chip (Prime Sense’s PS1080). offset of the captured pattern to the “known” pattern) in the image. Clearly, it uses a structured light technique: projecting a pattern into the scene, capturing the projected pattern from an offset point of view, and computing depth from disparity (i.e. It is not clear which methods are acutally in use. They discribe several possibilities for the capturing process, design and realization of the speckle pattern, and image processing. I searched through some of Prime Sense’s public patents and patent appliactions (e.g. Since people are starting to use the technology for a great variety of applications, some where accuracy is important, we should start thinking about this. We could reason about upper limits in accuracy, and possible problematic configurations that should be avoided.
#Kinect random dot pattern how to
However, understanding how the technology actually works can help reasoning about how to make even better use of it. I appreciate the work of Prime Sense, and I hope all their patents will make sure that they will earn what they deserve for such a great work. To make my point clear: I do not want to steal or reverse engineer any intellectual property, try to get into their business, or help anyone doing this. Since the day I heard of Microsoft’s Kinect, and especially the depth sensing technology developed by Prime Sense, I was wondering how it works.
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