I'm working on a smart camera that does key point prediction (predicting locations of wrists, elbow, shoulder, ears, eyes, nose, etc.) for gesture recognition.
Right now, the neural net is running on the embedded GPU (a Jetson TX2) and performance isn't ideal (<3 FPS). So I'm exploring whether it makes more sense to constantly upload images to the cloud, doing the predictions there, and sending the results back to the device.
I'm curious what approach others would recommend for a smart camera. Specifically:
- Performance differences between using an embedded GPU vs. the cloud?
- Cost differences between using an embedded GPU vs. the cloud?
- What other smart cameras are doing (Nest, Lighthouse, etc.)?
- If there is an alternative better than the Jetson TX2 if going the embedded path?
Any advice for any of the questions would be great.