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Interactive Projections

 WORK IN PROGRESS 

If you're interested in creating an interactive wall or floor projection, the first step would be to map the space and track anyone within it. This can be done in a variety of different ways, this tutorial will briefly introduce you to 3 mains techniques: 

Position tracking with LiDAR sensor

LiDAR technology can scan large areas by targeting a surface with a laser and measuring the time for the reflected light to return to the receiver; A Slamtec's RPLidar is a small scanner available for students to be used within the lab. The sensor requires a bit of prior set up to run, please allow some time for this process when planning the timeline of your project. 

Windows

For Windows 10 and 11,  begin by downloading Visual Studio, make sure you download the C++ app dev. Download the following GitHub repo: https://github.com/thepelkus-too/SlamtecLidarTDCPPCHOP. Unzip the folder and double click on the 'rplidar_sdk' folder, if empty download this repo (https://github.com/thepelkus-too/rplidar_sdk/tree/531cb0d1ef4bd95ccc3ed0a249787838836339f7) and paste it's content within your 'rplidar_sdk' folder. Now that your 'SlamtecLidarTDCPPCHOP-master' folder is ready, right-click on it and open in using VS Code. On the right hand side of the interface, look for 'CPlusPlusCHOPExample.sln' and double click on it. At this point VS Code will begin building your C++ solution, press OK if a pop-up window comes up. Check the terminal to find out if your built is completed. Please follow this tutorial for further instructions: https://youtu.be/fAvF2niosNA?si=8FYoHdmTat231lBA&t=626 - be aware that in the tutorial he calls it Visual Studio Code but it's Visual Studio you need!

Mac

Some Mac users will have it easier, but this plugin might not work on your laptop as it's only been tested out on my personal devices. Download the C++ plugin and read through the instructions to get started: https://github.com/creativetechnologylab/LiDAR-Sensor.

Object detection and tracking in OpenCV
Depth Sensing with OAK-D cameras