Maximum Volume Constrained Graph Nonnegative Matrix Factorization for Facial Expression Recognition
Viet-Hang Duong, Manh-Quan Bui, Jian–Jiun Ding, Bach-Tung Pham, Pham The Bao, Jia‐Ching Wang · IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences · 2017
In this work, two new proposed NMF models are developed for facial expression recognition. They are called maximum volume constrained nonnegative matrix factorization (MV_NMF) and maximum volume constrained graph nonnegative matrix factorization (MV_GNMF). They achieve sparseness from a larger simplicial cone constraint and the extracted features preserve the topological structure of the original images.