The invention discloses an age interference resistant face recognition method, which adopts an end-to-end non-cascade structure deep convolutional neural network to perform feature extraction and facerecognition on pictures of the same person at different age stages, and comprises the following steps of obtaining the pictures through an age-crossing face database, and forming a training set and atest set; expanding the data by adopting a data set increasing method to form a training image; establishing the end-to-end non-cascade structure deep convolutional neural network containing seven convolutional layers, three maximum pooling layers, one full connection layer and one softmax layer, and performing network training on the end-to-end non-cascade structure deep convolutional neural network; extracting the deep abstract features of the faces through a deep neural network to carry out face recognition, so that the method has the advantages of considering the time and performance, hasbetter adaptability to the face angle, the illumination intensity and the shielding degree, effectively overcomes the influence of age change on the face recognition, and improves the cross-age facerecognition precision.
Age interference resistant face recognition method