Technical Specifications

Face Detection

  • Robust frontal face detection
  • Detection of multiple faces in a photo
  • Head rotation support:  –30..30 degrees of in-plane rotation and –30..30 degrees out-of-plane rotation
  • Determines in-plane face rotation angle
  • Detection speed:
    • Realtime detection (webcam resolution, –15..15 degrees of in-plane head rotation): 0.0009 seconds (1111 FPS) (Intel*), 0.0011 seconds (909 FPS) (iOS*), 0.006 seconds (166 FPS) (Android*)
    • Reliable detection (digital camera resolution, –30..30 degrees of in-plane head rotation): 0.014 seconds (Intel), 0.037 seconds (iOS), 0.19 seconds (Android)
  • Returned information for each detected face: (x,y) coordinates of face center, face width and rotation angle
  • Easy configuration of face detection parameters

Face Matching

  • Matching of two faces at given FAR (False Acceptance Rate) and FRR (False Rejection Rate)
  • Enrollment time:
    • Webcam resolution, using FSDK_GetFaceTemplate: 0.015 seconds (67 FPS) (Intel), 0.026 seconds (38 FPS) (iOS), 0.14 seconds (7 FPS) (Android)
  • Template Size: 1040 bytes
  • Matching speed:
    • Single thread, templates per second: 3571428 (Intel), 3205128 (iOS), 93284 (Android)
    • Multiple parallel threads, templates per second: 26595745 (Intel), 10948905 (iOS), 287811 (Android)
  • Returned information: facial similarity level
  • ROC Diagram

Live Video Recognition with Tracker API

  • Assigns a unique ID to each subject detected in video
  • Allows tagging any subject in video with a name, and recognizing it further
  • No requirement for a subject to pose to be enrolled
  • Constant learning of subjects’ appearance
  • Provides with estimates of false acceptance rate and recognition rate
  • Tracks multiple faces and their facial features
  • Recognizes male and female genders
  • Recognizes age
  • Recognizes facial expressions

Facial Feature Detection

  • Detection of 70 facial feature points (eyes, eyebrows, mouth, nose, face contour)
  • Detection time (using FSDK_DetectFacialFeaturesInRegion, not including face detection stage): 0.00054 seconds (1851 FPS) (Intel), 0.00055 seconds (1818 FPS) (iOS), 0.004 seconds (250 FPS) (Android)
  • Allowed head rotation: –30..30 degrees of in-plane rotation, –20..20 degrees out-of-plane rotation
  • Returned information: array of 70 (x,y) coordinates of each facial feature point

Eye Centers Detection

  • Detection of eye centers only, detection time (not including face detection stage): 0.00054 seconds (1851 FPS) (Intel), 0.00051 seconds (1960 FPS) (iOS), 0.004 seconds (250 FPS) (Android)
  • Returned information: two (x,y) coordinates of left eye center and right eye center

Gender Recognition

  • Recognition of different genders
  • Gender recognition time (not including face and facial feature detection stages): 0.0052 seconds (Intel), 0.0076 seconds (iOS), 0.015 seconds (Android)
  • Returned information: confidence level in each gender

Age Recognition

  • Recognition of age
  • Age recognition time (not including face and facial feature detection stages): 0.0056 seconds (Intel), 0.014 seconds (iOS), 0.016 seconds (Android)
  • Returned information: age of a person
  • Depending on source quality and lighting conditions, error rate is +/- 5 years

Expression Recognition

  • Recognizes if the subject smiles and if the eyes are open or closed
  • Expression recognition time (not including face and facial feature detection stages): 0.0052 seconds (Intel), 0.008 seconds (iOS), 0.015 seconds (Android)
  • Returned information: confidence level in each expression

Multi-Core Support

  • The library uses all available processor cores when executing face detection or recognition functions, to maximize the performance.

Library Size

  • The size of the redistributables does not exceed 110 MB for each platform.

* Measured on Intel Xeon 8124M processor with 8 threads, iPhone X with 6 threads, Xiaomi mi5 (Snapdragon 820) with 4 threads.

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