Quasistatic Cavity Resonance for Ubiquitous Wireless Power Transfer

I mean, the issue with cameras on everyone is that they all require small batteries, meaning always recording with them isn't really practical. There is already early-stage research into long-range wireless charging ▶ this video so maybe 15+ years in the future it would be practical to have always-recording devices.

That is doable right now. I am only sort of being glib here. I just want to outline what's involved in what people think is a simple task in a spatial system. TLDR: As of right now, your wildest dreams are pretty possible. In the next 2 years, how we compute is going to get strange. Nothing is nearly as simple in an XR environment as a traditional computing one and currently most people don't really want what they'd ask for. Building a simple (useful) XR app makes launching a web product look like assembling a lego set vs. landing on the moon. --------- Imagenet[0] works just fine for the object identification. You would probably want to use RGBd sensors like the kinect[1] or Intel Realsense[2] instead of regular cameras, but tracking like what the Vive[3] uses could also work. The thing you just proposed would involve a network of server processes handling the spatial data and feeding extracted relevant contextual information to a wireless headset at a pretty crazy rate. Just to give you an idea a SLAM[4] point cloud from a stereo set of cameras or a cloud from a Kinect2 or Realsese produces a stream of data that is about 200mb a second. Google Draco[5] can compress that and help you stream that data at 1/8 the size without any tuning. Extracting skeletal information from that is really something that only Microsoft has reliably managed to deliver and it's at the core of the Kinect/Hololens products. NuiTrack[6] is the next best thing, but registering a human involves a T-Po

If you're having trouble loading the page, here is the direct link to the PDF: link Here are the YouTube videos: ▶ this video link