Facial Recognition Suite

We bet this is something that even your 6 year old nephew has heard of. Yes, face recognition is ubiquitous but it is far from being easily accessible. From Facebook’s automated tagging to iPhone X’s FaceID, face recognition has been deployed in numerous applications and has had tremendous success. With applications ranging from entertainment, banking and finance to security, face recognition systems have proved to stand the test of time.

We believe that given the recent paradigm shift towards adoption of technology and the wide range of applications, a plug and play face recognition system is the need of the hour. Our objective of giving businesses and developers easy access to deploy a state-of-the-art face recognition system within minutes was achieved with the release of our face module, Visage. Visage or French for face is an umbrella module consisting of multiple services based on face detection and recognition.

Continue reading to understand how Visage can help your business ...

Emotion Detection


The human face plays a prodigious role for automatic recognition of emotion in the field of identification of human emotion and the interaction between human and computer for some real applications like driver state surveillance, market research, brand and product perception, health monitoring etc.

Emotion detection from facial expressions serves as a practical alternative to measure a consumer’s feedback and engagement with content, products and brands in general. When feedback is taken in this format, it is genuinely non-intrusive in addition to it being more reliable and objective than other forms.

Detect emotion from facial expressions. Categorise into Neutral, Surprised, Sad, Angry, Happy, Fearful and Disgusted.

Gender Detection

Age and gender play fundamental roles in social interactions. It is observable that our behavior and social interaction are greatly influenced by genders of people whom we intend to interact with. Hence a successful gender recognition system could have great impact in improving human computer interaction systems in such a way as to make them be more user-friendly and acting more human-like.

Despite the basic roles these attributes play in our day-to-day lives, the ability to automatically estimate them accurately and reliably from face images is still far from meeting the needs of commercial applications. This is particularly perplexing when considering recent claims to super-human capabilities in the related task of face recognition

Detect user gender from faces and classify them into Male/Female to serve them better.