The invention discloses a method for identifying multi-view human face based on nonlinear 
tensor resolution and view manifold, which comprises the following steps: normalizing the size of the multi-view human face; dividing multi-view human face images into a 
test set and a 
training set by adopting a method of leaving one out; arraying the human face images in the 
training set into a form of 
tensor along the direction of identity, view and pixel information change, resolving 
tensor data by using high-order singular values to obtain a 
coefficient matrix of identity, view and pixel factors of the human face images; using a data-concept 
driving mode to array and interpolate view coefficients to obtain the view manifold of human face; according to the rotating objective sequence of the human face, generating the view manifold through a concept 
driving mode; using the nonlinear tensor resolution to map the view manifold to a 
data space of the multi-view human face, obtaining a modular matrix of identity coefficient, and establishing a model of the multi-view human face; and adopting an iterative 
algorithm based on EM-like to solve a 
model parameter, and achieving identification by the parameter meeting the minimum reconstructed error criterion. The method has the advantages of high accuracy and high speed, and can be used for complex human face retrieval and identification under different view angles in the field of biological characteristic identification.