The invention relates to a face identification method based on an independent component analysis network. The method comprises the following steps: 1) carrying out cutting, aligning and normalizationpretreatment on input face images; 2) carrying out filtering through a group of trained ICA filters to obtain a group of mapping images; 3) carrying out non-linear and pooling processing on each mapping image to obtain a more efficient feature mapping image; 4) carrying out block LBP coding on each mapping image, and then, stringing the obtained local features to obtain feature expression; and 5)carrying out WPCA dimension reduction on the feature expression, and finally, carrying out identification verification on the two pieces face images through a cosine similarity measurement method. Thetrained ICA filters are applied to a CNN to form a single network; multi-scale information can be obtained based on different sensing areas of the ICA filters; and the method can ensure higher recognition rate in face recognition, and meanwhile, reduces calculation amount effectively and is convenient for popularization and application.