Seeing The World Through Depth Sensing Cameras

The Oculus Rift and all the other 3D video goggle solutions out there are great if you want to explore virtual worlds with stereoscopic vision, but until now we haven’t seen anyone exploring real life with digital stereoscopic viewers. [pabr] combined the Kinect-like sensor in an ASUS Xtion with a smartphone in a Google Cardboard-like setup for 3D views the human eye can’t naturally experience like a third-person view, a radar-like display, and seeing what the world would look like with your eyes 20 inches apart.

[pabr] is using an ASUS Xtion depth sensor connected to a Galaxy SIII via the USB OTG port. With a little bit of code, the output from the depth sensor can be pushed to the phone’s display. The hardware setup consists of a VR-Spective, a rather expensive bit of plastic, but with the right mechanical considerations, a piece of cardboard or some foam board and hot glue would do quite nicely.

[pabr] put together a video demo of his build, along with a few examples of what this project can do. It’s rather odd, and surprisingly not a superfluous way to see in 3D. You can check out that video below.

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Charlotte, the hexapod with 3D vision

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Charlotte’s chassis comes from as a kit, but the stock electronics are based on an Arduino – not something for a robot that needs to run computer vision apps. [Kevin] ended up using a Raspi for the controller and gave Charlotte eyes with an Asus XTION. Edit: or a PrimeSense sensor These sensors are structured light depth cameras just like the kinect, only about smaller, lighter, and have a better color output.

Hardware is only one half of the equation, so [Kevin] tossed the Arduino-based stock electronics and replaced them with a Raspberry Pi. This allowed him to hone his C++ skills and add one very cool peripheral – the XTION depth camera.

To the surprise of many, we’re sure, [Kevin] is running OpenNI on his Raspberry Pi, allowing Charlotte to take readings from her depth camera and keep from colliding into any objects. The Raspberry Pi is overclocked, of course, and the CPU usage is hovering around 90%, but if you’re looking for a project that uses a depth sensor with a Pi, there you go.

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