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This appears to be what powers the basic face detection in the Vision framework, not what powers Face ID: https://developer.apple.com/documentation/vision https

This appears to be what powers the basic face detection in the Vision framework, not what powers Face ID: https://developer.apple.com/documentation/vision https://developer.apple.com/documentation/vision It is not capable of identifying individual people, just recognizing faces and facial features in an image. Still quite useful for things like Snapchat's masks.

trumpeta 9y ago
In my limited trials it was not terribly performant, running at 15fps or so only.
- ctlaltdefeat 9y ago
  I would consider that pretty performant for a task such as this on a phone.
  - cycrutchfield 9y ago
    Compared to non-DNN techniques? I don’t have concrete numbers but I’m pretty sure “classical” techniques can do this with much higher throughput.
    - tedunangst 9y ago
      With equal accuracy?
      - tzs 9y ago
        If the non-NN techniques are faster, but the NN techniques are more accurate, couldn't they be combined to provide both speed and accuracy? Use the NN to find the faces, and the non-NN to track faces once the NN has found them, and use the NN to periodically check to see that the non-NN is still locked on.
        tedunangst 9y ago
        Does that work? A NN might detect half a face, but then how do you switch over to the "find two dots" technique when there's only one eye? This seems susceptible to a lot of flapping.
        tzs 9y ago
        I'd expect that the non-NN part would be more of a "track movement of this arbitrary blob" thing rather than a "track movement of this face" thing. Suppose the NN is only 25% of the speed you need to support the frame rate you want. Then every time you get a new face blob list from the NN, the non-NN tracker would to track the blobs for 3 frames. My guess is that in most common photography situations where you need face detection, faces won't move very far or won't change orientation or lighting very much in 3 frames.
- bpicolo 9y ago
  On what device? The A11 chip is far more performant than previous gens.
GeekyBear 9y ago
It was also used to assist blind users in their efforts to use the built in camera app. >VoiceOver will then use face detection to tell you how many people are in the frame. It will also say if a face is small, and where in the frame a face or faces are located incase you want to try and better center them. When you move, it will tell you the new framing, so you can figure out if you're getting closer to the shot you want. One face. Small face. Bottom left corner. https://www.imore.com/making-iphone-camera-work-blind https://www.imore.com/making-iphone-camera-work-blind
rahimnathwani 9y ago
Does this work better than Google's on-device face detection? I was experimenting with it yesterday and it seems to work pretty well, even in low light. https://developers.google.com/android/reference/com/google/android/gms/vision/face/Face https://developers.google.com/android/reference/com/google/a...

trumpeta 9y ago

In my limited trials it was not terribly performant, running at 15fps or so only.

ctlaltdefeat 9y ago
I would consider that pretty performant for a task such as this on a phone.
- cycrutchfield 9y ago
  Compared to non-DNN techniques? I don’t have concrete numbers but I’m pretty sure “classical” techniques can do this with much higher throughput.
  - tedunangst 9y ago
    With equal accuracy?
    - tzs 9y ago
      If the non-NN techniques are faster, but the NN techniques are more accurate, couldn't they be combined to provide both speed and accuracy? Use the NN to find the faces, and the non-NN to track faces once the NN has found them, and use the NN to periodically check to see that the non-NN is still locked on.
      - tedunangst 9y ago
        Does that work? A NN might detect half a face, but then how do you switch over to the "find two dots" technique when there's only one eye? This seems susceptible to a lot of flapping.
        tzs 9y ago
        I'd expect that the non-NN part would be more of a "track movement of this arbitrary blob" thing rather than a "track movement of this face" thing. Suppose the NN is only 25% of the speed you need to support the frame rate you want. Then every time you get a new face blob list from the NN, the non-NN tracker would to track the blobs for 3 frames. My guess is that in most common photography situations where you need face detection, faces won't move very far or won't change orientation or lighting very much in 3 frames.
bpicolo 9y ago
On what device? The A11 chip is far more performant than previous gens.

GeekyBear 9y ago

It was also used to assist blind users in their efforts to use the built in camera app. >VoiceOver will then use face detection to tell you how many people are in the frame. It will also say if a face is small, and where in the frame a face or faces are located incase you want to try and better center them. When you move, it will tell you the new framing, so you can figure out if you're getting closer to the shot you want. One face. Small face. Bottom left corner. https://www.imore.com/making-iphone-camera-work-blind https://www.imore.com/making-iphone-camera-work-blind

rahimnathwani 9y ago

Does this work better than Google's on-device face detection? I was experimenting with it yesterday and it seems to work pretty well, even in low light. https://developers.google.com/android/reference/com/google/android/gms/vision/face/Face https://developers.google.com/android/reference/com/google/a...