5 ms·

How fast are the algorithms? does anyone of them work in real time?

• prats226 7y ago
  They should work in real time. Atleast the architecture looks like end to end neural network so just like other CNN based models, this should as well work in real time after quantization etc
• jayd16 7y ago
  They showed an app like this running on a phone in laggy but real time at I/O yesterday
  • manneshiva 7y ago
    Interesting, wonder what their use case was?
    • jayd16 7y ago
      Just a fun dance recognition app to show off ML.
    • prats226 7y ago
      If it was in google IO, it will be some consumer use case probably? Althought there are a lot of commercial use cases of this technology. For example, you can train a simple classifier on top of pose which will help you record time spent on different types of activities which is useful in measuring productivity.
    • ChuckMcM 7y ago
      I can think of a couple of use cases, none of them particularly useful though. Imagine you had the pose data for the image and the pose data of someone else, even an imaginary someone else thanks to GaNs.
    • amelius 7y ago
      Dance Dance Revolution, but without the sensor mat? https://en.wikipedia.org/wiki/Dance_Dance_Revolution https://en.wikipedia.org/wiki/Dance_Dance_Revolution
  • prats226 7y ago
    Yeah nowadays with post-training quantization techniques as well as things like squeezenet which is quantization aware training technique, models are becoming fairly small to be able to run on phone smoothly
• czr 7y ago
  Certainly. For example, https://storage.googleapis.com/tfjs-models/demos/posenet/camera.html https://storage.googleapis.com/tfjs-models/demos/posenet/cam... will run in your browser. https://github.com/CMU-Perceptual-Computing-Lab/openpose https://github.com/CMU-Perceptual-Computing-Lab/openpose is also a decent choice for realtime pose estimation, although I'm not sure if they have a web demo anywhere.