Face recognition and description for - Politecnico di Milano · 2018. 2. 27. · email:...
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2/26/2018 1 Imaging and Vision Laboratory Università di Milano-Bicocca web: www.ivl.disco.unimib.it email: [email protected] Raimondo Schettini Face recognition and description for IoT applications The Home‐IoT and Teinvein projects Video‐based driver drowsiness and stress monitoring Video based action recognition and anomaly detection (car and home environments) Short‐ and Long‐term video‐ based healthiness monitoring Sensor‐based action recognition and anomaly detection
Transcript of Face recognition and description for - Politecnico di Milano · 2018. 2. 27. · email:...
2/26/2018
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Imaging and Vision LaboratoryUniversità di Milano-Bicoccaweb: www.ivl.disco.unimib.itemail: [email protected]
Raimondo Schettini
Face recognition and description for IoT applications
The Home‐IoT and Teinvein projects
Video‐based driver drowsiness and stress monitoring
Video based action recognition and anomaly detection (car and home environments)
Short‐ and Long‐term video‐based healthiness monitoring
Sensor‐based action recognition and anomaly detection
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• For face detection, recognition, description …
can we use solutions in the state‐of –the art ?
The Home‐IoT and Teinvein projects
Examples of Google Picasa face detections
Detected faces are visible in the right columns
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Multi‐task AffectNet
Input image
Valence
Arousal
‐1 (low) 1 (high)
‐1 (negative)
1 (positive)
0%
100%
50%
Landmark
Emotion
Valence
Arousal
Output
Happiness
Short‐ and Long‐term video‐based healthiness monitoring using Multi‐task Affect‐Net
But… how can we be sure that the system is recording date of the same person ?
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Face verification
Large Age‐Gap Face Verification
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Our CNN immediately said it !
You will find some of our solutions for face detection and recognition in the next release of Canon Lifecake app
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3D face recognition on IPhone X
Original iPhoneX commercial
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iPhoneX faceID fail
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IVL processing – both IDs enrolled
IVL processing – only one ID enrolled
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Facial attributes estimation by multi‐task CNNs
EyebrowsArchedBushy
Narrow EyeEyeglasses
Bags Under Eyes
HairBlackBlondBrownGrayStraightWavy
BangsBald
Receding Hairline
Wearing Hat
NoseBigPointy Attractive
BlurryChubbyOval FaceSideburnsRosy CheeksHigh CheekbonesPale SkinHeavy MakeupWearing Earrings
Wearing Necklace
Wearing Necktie
Big LipsMouth Slightly OpenSmilingWearing Lipstick
5 o’clock Shadow
Double ChinNo BeardGoateeMustache
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● Predict biometrics such as: age, gender, ethnicity● Distinguish among, for example, hair color, types of
beards, or hair styles● Assess the presence/absence of accessories, namely
eyeglasses, hat, earrings
Face attributes
Facial attributes estimation by multi‐task CNNs
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Face attributes
Facial attributes estimation by multi‐task CNNs
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IVL processing – face attributes
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3D faces
Face Detection using Curvature Analysis, (Alessandro Colombo, Claudio Cusano, Raimondo Schettini) In Pattern Recognition, volume 39, number 3, pp. 444‐455, Elsevier, 2006.
Is it time to come back to future (3d) ?
Imaging and VisionImaging and Visionwww.ivl.disco.unimib.it
We are hiring master students, Phd students, post-doc and RTD-A
