Human emotion recognition using the adaptive sub-layer-compensation based facial edge detection

In this paper, we propose an adaptive sub-layer compensation (ASLC) based facial edge detection for human emotion recognition. We modify the Marr-Hildreth edge detector with Wiener filtering, sub-layer compensation and hysteresis analysis to compensate the negative effects of the Laplacian of Gaussian (LoG) operator such as image degradation, high response to unwanted details, and disconnected edges. We investigate a Discriminative Isomap (D-Isomap) based approach that combines the ASLC feature and deformable elastic body spline (EBS) feature for the final decision. RML emotion database and Cohn-Kanade database are used for the experiment and the results demonstrate the effectiveness of the proposed method.