We use the MobileNet model to identify gender, while the AffectNet model is used to detect emotion. Facial key point detection is achieved using Google's Mobile Vision API.
Neural networks and deep learning have sparked tremendous progress in the field of natural language processing (NLP) and computer vision. While many of the face, object, landmark, logo and text recognition technologies are provided for internet-connected devices, we believe that the ever-increasing computational power of mobile devices can enable the delivery of these technologies into the hands of users, anytime, anywhere, regardless of internet connection. However, computer vision for on device and embedded applications face many challenges—models must run quickly with high accuracy in a resource-constrained environment making use of limited computation, power, and space.
TensorFlow offers various pre-trained models, such as drag and drop models, in order to identify approximately 1,000 default objects...