Face Detection Performance

Sighthound's face detector performs better than any other publicly available face detection algorithm, including commercial competitors and an open source alternative. Benchmarked using the BAO and Annotated Faces in the Wild (AFW) publicly available data sets containing over 1,700 faces from 600 images, Sighthound's face detector has both the lowest number of false detections and the highest number of correct detections. You can try the face detector in the Sighthound Cloud service.

  
    
    True Positive (TP)
    False Positive (FP)
    False Negative (FN)
    Precision = TP/(TP+FP)
    Recall = TP/(TP+FN)
  

  Sighthound
  1590
  5
  184
  99.69%
  89.63%
  

  	Google Cloud
  	1575
  	5
  	199
  	99.68%
  	88.78%
  

  	Microsoft Research
  	1370
  	5
  	404
  	99.64%
  	77.23%
  

  	Face++
  	1412
  	6
  	362
  	99.58%
  	79.59%
  

  	Kairos
  	1187
  	37
  	587
  	96.98%
  	66.91%
  

  	OpenCV
  	1452
  	278
  	322
  	83.93%
  	81.85%
  

Definitions
TP: number of identified faces that are correct
FP: number of identified faces that are incorrect
FN: number of missed faces
Precision: percent of identified faces that are correct
Recall: percent of correctly identified faces to the total number of faces