How do you use OpenCV to capture and image process frames so that you can build computer vision applications under Linux on the Beaglebone – I do this using the boneCV.cpp program as described below. This code uses the OpenCV library which is available on the Angstrom distribution of the Beaglebone. Finally, I write a small program boneCVtiming.cpp to test the performance of the Beaglebone black for capturing and processing image data.
The combination of Omek Beckon and the BeagleBoard-xM provides developers with a low-cost solution for adding gesture recognition to devices using embedded processors, and is an ideal solution for educators and independent developers looking to research or experiment with gesture recognition.
Want to take 3D pictures? Need cool things to make with your 3D printer? This 3D camera build uses a Structured lighting technique to create a 3D representation that can be rendered with any 3D software. Structured lighting is basically a set of images that are sequentially projected onto a scene and captured with an ordinary CMOS camera. The deformation of the structured light is ran though an algorithm to determine the depth at each pixel. The resulting X,Y and Z coordinates (3D point cloud) are used to reproduce a 3D model of the scene.