Facial Expression Recognition Using Adaptive Robust Local Complete Pattern
An effective face descriptor is a significant element of a perfect facial expression recognition system. In this paper, we propose a new face descriptor, Adaptive Robust Local Complete Pattern (ARLCP) ARLCP effectively encodes significant information of emotion related features by using the sign, magnitude and directional information of edge response that is more robust to noise and illumination variation. In this histogram based approach, obtained feature image is divided into several regions, histogram of each region is computed independently and all histograms are concatenated to generate a final feature vector. We have experimented our method on several datasets using cross validation schemes to evaluate the performance. From those experiments, it is evident that our method (ARLCP) provides better accuracy in facial expression recognition.
2019 IEEE International Conference on Image Processing (ICIP)