
Lightweight & fast
Low data size and memory usage ensure fast but yet accurate gender, age and emotion estimation in milliseconds (view references).
Low data size and memory usage ensure fast but yet accurate gender, age and emotion estimation in milliseconds (view references).
Face analysis works flawlessly on any device, both online and offline.
No personal data such as photos or names is stored or processed by default, ensuring privacy.
Integration is a breeze with the detailed guides and samples we’ve compiled during 10+ years of development and research.
FaceAnalysis detects faces in images or video and then uses face tracking and action units to accurately provide gender, emotions and age for the faces in roughly frontal position.
There are certain common features in human faces that distinguish male faces from female ones. FaceAnalysis uses advanced machine learning techniques to provide you with gender detection.
Landmarks such as the location of the pupils, eye corners, lip boundaries, etc. change with age. Our algorithm was trained on a large database of different faces to detect the approximate age of a person based on such features.
Emotion estimation detects facial expressions from images or video and returns the probability distribution of each of the six universal emotions: happiness, sadness, anger, fear, surprise, and disgust, and additionally neutral.