关键词: 统一局部二值模式, 单样本, 特征提取, 多流形判别分析

Abstract: In order to effectively extract facial expression feature in the single face recognition system, this paper proposes a novel method by fusing Uniform LBP features and  Discriminative Multi-Manifold Analysis（DMMA） features. Each face image is partitioned into several nonoverlapping patches to form an image set for each sample per person. The Uniform Local Binary Pattern（Uniform LBP） operator is used to extract image histogram of each image set. So the histogram of each image set forms a statistics manifold. This paper applies DMMA algorithm to obtain the low-dimensional face image feature. It uses the reconstruction-based manifold-manifold distance to identify the unlabeled face images. Experimental results show that the algorithm is superior to the general recognition DMMA algorithms on the AR database and ORL database.

Key words: uniform local binary pattern, single sample, feature extraction, Discriminative Multi-Manifold Analysis（DMMA）