Facial Expression Recognition Based on Semi-Supervised Local Linear Embedding
Ming Wei · Journal of Shenyang Jianzhu University · 2008
In order to incorporate semi-supervised learning and manifold learning,especially to recognize facial expression,a new semi-supervised manifold learning for facial expression recognition is proposed.This method relied on the distance matrix formed by both labeled and unlabeled samples,and then the local linear embedding(LLE) method was used to extract discriminative manifold features according to the modified distance matrix.The proposed method produces better classification performance which captures the intrinsic manifold structure collectively revealed by labeled and unlabeled samples.Experimental results on public facial expression databases show that the proposed method can improves facial expression classification performance effectively.