A framework for joint facial expression recognition and point localization
Anwar Saeed, Ayoub K. Al-Hamadi · 2016
Unlike many approaches that use detected facial points to infer facial expressions, in this work, we propose an approach in which we jointly tackle the two tasks on a frame basis. After ensuring the consistent face cropping, our framework makes use of geometric- and appearance-based methods for the facial expression recognition, and of cascade regression and local-based methods for the facial point detection. For the data fusion, we adapted the Viterbi algorithm. The training and testing were carried out on two public benchmark databases. With the proposed framework, we improved the recognition rate of the facial expression and the accuracy of the facial point localization by at least 5.4% and 8.9%, respectively, in comparison to the conventional sequential methods.