作者
Gaoyun An, Shuai Liu, Qiuqi Ruan
发表日期
2017/5
期刊
Pattern Analysis and Applications
卷号
20
页码范围
453-471
出版商
Springer London
简介
In this paper, a novel sparse neighborhood preserving non-negative tensor factorization (SNPNTF) algorithm is proposed for facial expression recognition. It is derived from non-negative tensor factorization (NTF), and it works in the rank-one tensor space. A sparse constraint is adopted into the objective function, which takes the optimization step in the direction of the negative gradient, and then projects onto the sparse constrained space. To consider the spatial neighborhood structure and the class-based discriminant information, a neighborhood preserving constraint is adopted based on the manifold learning and graph preserving theory. The Laplacian graph which encodes the spatial information in the face samples and the penalty graph which considers the pre-defined class information are considered in this constraint. By using it, the obtained parts-based representations of SNPNTF vary smoothly …
学术搜索中的文章
G An, S Liu, Q Ruan - Pattern Analysis and Applications, 2017