Survey on data dimensionality reduction for face image based on graph theory
Yan Zhang · Electronic Design Engineering · 2013
With the method based on graph theory has gotten more and more attention in recent years,to reduce the high dimensionality of data is the core problem in face recognition.The paper introduces the basic concept of graph theory,summarizes different kinds of methods about dimensionality reduction for face image,which can be unified to graph embedding framework.Then it analyses the advantages and disadvantages of all kinds of algorithm in the linear and nonlinear respect,and concludes that the mathod of nonlinear graph embedding has better function in both nonlinear respect and data dimensionality reduction than traditional ways.Finally,the paper discusses the development in the future according to the existing ways of graph construction.