Face Analysis includes machine learning algorithms to determine gender, emotions and age. Face Analysis is compatible with Face Track to find/track faces in images or video, determine gender, emotions, and age for a specified face.
Face Recognition is used to identify or verify a person from a digital image or a video source using a pre-stored facial data. Visage SDK's face recognition algorithms can measure similarities between people and recognize a person’s identity[citation needed] from a frontal facial image by comparing it to pre-stored faces.
The development of Visage SDK began in 2002 when Visage Technologies AB was founded in Linköping, Sweden. The founders were among the contributors to the MPEG-4 Face and Body Animation International Standard.[4][5]
Tracks multiple faces and facial features in input video, images or in real time[6]
Returns 2D and 3D head pose, the coordinates of facial feature points (e.g. chin tip, nose tip, lip corners, mouth contour, chin pose, eyebrow contours), fitted 3D face model, and eye closure and eye rotation (gaze direction)
Tracking begins immediately when a face is detected
Recovery from fidelity loss due to occlusions, head rotation, or other errors
Automatic detection of separate people in front of the camera
^Pandžić, Igor and Robert Forchheimer (2002): "The origins of the MPEG-4 Facial Animation standard", in: MPEG-4 Facial Animation - The standard, implementations and applications (eds. Igor S. Pandžić and Robert Forchheimer). Chichester: John Wiley & Sons (ISBN0-470-84465-5).
^Pandžić, Igor and Robert Forchheimer (2002): "MPEG-4 Facial Animation Framework for the Web and Mobile Platforms", in: MPEG-4 Facial Animation - The standard, implementations and applications (eds. Igor S. Pandžić and Robert Forchheimer). Chichester: John Wiley & Sons (ISBN0-470-84465-5)
