3. Similarity function
β’ Degree of difference between images
π π₯ =
same, π πππ1, πππ2 < π
different, π πππ1, πππ2 β₯ π
4. Siamese Network
β’ Mapping from image to Euclidian Space (encoding)
β’ The encoding used for face verification, recognition and Clustering
128
5. β’ An Image is converted to an encoding of size 128
β’ Images compared using encodings of two faces
SN
SN
π π₯ π , π₯ π = f π₯ π β f π₯ π 2
π¦ = 1 ππ π < π πππ π 0
9. Face Recognition
β’ Extension of Face Verification
β’ Each identity has there corresponding encoding pre-saved
β’ Incoming image is compared with each encoding
β’ Output: The least distance if less than threshold
11. Address to slides
Address to slides
https://www.slideshare.net/nemishkanwar5/face-verification-and-
recognition
Find me on Linkedin @
https://www.linkedin.com/in/nemishkanwar/