mirror of https://github.com/vladmandic/human
33 lines
1.2 KiB
Markdown
33 lines
1.2 KiB
Markdown
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# Human Face Recognition
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`facerecognition` runs multiple checks to validate webcam input before performing face match, similar to *FaceID*
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## Workflow
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- Starts webcam
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- Waits until input video contains validated face or timeout is reached
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- Number of people
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- Face size
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- Face and gaze direction
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- Detection scores
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- Blink detection (including temporal check for blink speed) to verify live input
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- Runs antispoofing optional module
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- Runs liveness optional module
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- Runs match against database of registered faces and presents best match with scores
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## Notes
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Both `antispoof` and `liveness` models are tiny and
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designed to serve as a quick check when used together with other indicators:
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- size below 1MB
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- very quick inference times as they are very simple (11 ops for antispoof and 23 ops for liveness)
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- trained on low-resolution inputs
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### Anti-spoofing Module
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- Checks if input is realistic (e.g. computer generated faces)
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- Configuration: `human.config.face.antispoof`.enabled
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- Result: `human.result.face[0].real` as score
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### Liveness Module
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- Checks if input has obvious artifacts due to recording (e.g. playing back phone recording of a face)
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- Configuration: `human.config.face.liveness`.enabled
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- Result: `human.result.face[0].live` as score
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