A fast identity-independent expression recognition system for robust cartoonification using smart devices

Facial expressions convey rich information about emotions, intentions and other internal states of a person. Automatic facial expression and cartoonification systems are aiming towards the application of computer vision systems in human computer interaction, emotion analysis, medical care, virtual learning and even entertainment. In this paper, we propose an identity-independent robust system to detect human expression and generate their corresponding cartoonified images in real-time using smart-devices. Identity-independent expression recognition system enhances the facial features of query face image using its intra-class variation image and classifies using support vector machines. The method is robust to variation in identity and illumination of the query face image. Along with the basic expressions, like angry, happy and sad, we have also successfully detected the emotional states of sleepy and pain. The experimental results on JAFFE, CK+, PICS, Yalefaces, and Senthil databases show the effectiveness of the system.