System and method for segmenting facial wrinkle

An operating program of a facial wrinkle detection system, which is a computer program stored in a computer-readable recording medium for executing a facial wrinkle detection method on a computer by being coupled with the computer, wherein the facial wrinkle detection method comprises:

• converting each of predetermined number or more of collected images into RGB data, extracting RGB data of a facial region from the converted RGB data, and then deriving a correct texture map for the facial RGB data through a Gaussian filter;
• training a deep neural network with the facial RGB data and estimating a texture map;
• and
• training the deep neural network by changing a weight of the deep learning neural network by updating weights based on an MSE calculated from the difference between the estimated texture map and the ground truth texture map,
• wherein supervised learning stage comprises:
• deriving combined data by combining preprocessed wrinkle RGB data from fewer than a predetermined number of input images and a texture map derived from the wrinkle RGB data through the Gaussian filter, based on a channel-wise concatenation operation, deriving each of binary wrinkle data with a mask determined by at least one annotator for fewer than the predetermined number of the input images, and outputting a consolidated ground truth wrinkle data by combining each of the binary wrinkle data through a majority voting algorithm;
• estimating the wrinkle data through transfer learning of the deep neural network pre-trained on the basis of a weakly supervised learning device with the combined data as the inputs;
• and
• fine-tuning a weight of the pre-trained deep neural network based on a soft dice loss calculated from the difference between the estimated wrinkle data of a supervised learning module and the ground truth wrinkle data,
• wherein the supervised learning stage further comprises outputting optimal wrinkle data as a result of the transfer learning of the fine-tuned deep neural network.