Modern Dance Or Full-Body Keyboard? Why Not Both!

If you felt in your heart that Hackaday was a place that would forever be free from projects that require extensive choreography to pull off, we’re sorry to disappoint you. Because you’re going to need a level of coordination and gross motor skills that most of us probably lack if you’re going to type with this full-body, semaphore-powered keyboard.

This is another one of [Fletcher Heisler]’s alternative inputs projects, in the vein of his face-operated coding keyboard. The idea there was to be able to code with facial gestures while cradling a sleeping baby; this project is quite a bit more expressive. Pretty much all you need to know about the technical side of the project can be gleaned from the brilliant “Hello world!” segment at the start of the video below. [Fletcher] uses OpenCV and MediaPipe’s Pose library for pose estimation to decode the classic flag semaphore alphabet, which encodes characters in the angle of the signaler’s extended arms relative to their body. To extend the character set, [Fletcher] added a squat gesture for numbers, and a shift function controlled by opening and closing the hands. The jazz-hands thing is just a bonus.

Honestly, the hack here is mostly a brain hack — learning a complex series of gestures and stringing them together fluidly isn’t easy. [Fletcher] used a few earworms to help him master the character set and tune his code; the inevitable Rickroll was quite artistic, and watching him nail the [Johnny Cash] song was strangely satisfying. We also thoroughly enjoyed the group number at the end. Ooga chaka FTW.

Continue reading “Modern Dance Or Full-Body Keyboard? Why Not Both!”

Four images in one. Top left is an image of four individuals in a room with whiteboards and desks in the background along with various clutter on the floor. Over the people is a wireframe overlay of their poses. The image on the top right is just the wireframe people on a black background. Bottom left image is of a single individual standing in a room with the pose wireframe overlay. Bottom right image is the single pose wireframe on a black background.

Tracking Humans With WiFi

In case you thought that cameras, LiDAR, infrared sensors, and the like weren’t enough for Big Brother to track you, researchers from Carnegie Mellon University have found a way to track human movements via WiFi. [PDF via VPNoverview]

The process uses the signals from WiFi routers for an inexpensive way to determine human poses that isn’t hampered by lack of illumination or object occlusion. The system produces UV coordinates of human bodies by analyzing signal strength and phase data to generate a 2D feature map and then feeding that through a modified DensePose-RCNN architecture which corresponds to 3D human poses. The system does have trouble with unusual poses that are not in the training set or if there are more than three subjects in the detection area.

While there are probably applications in Kinect-esque VR Halo games, this will probably go straight into the toolbox of three letter agencies and advertising-fueled tech companies. The authors claim this to use “privacy-preserving algorithms for human sensing,” but only time will tell if they’re correct.

If you’re interested in other creepy surveillance tools, checkout the Heat-Sensing Crotch Monitor or this Dystopian Peep Show.