Asian human face age characteristic model generating method and aging estimation method

Abstract

The invention provides an Asian human face age characteristic model generating method, and the method comprises the steps: S1), extracting a wrinkle difference characteristic pattern of each human face image in a training set, and obtaining an original feature vector of each human face image; S2), determining the number of reduced dimensions of each original feature vector, reducing the dimensions of the original feature vector of each original image based on a PCA method, and obtaining feature vectors after dimension reduction; S3), carrying out the training of the feature vectors based on a support vector machine regression algorithm after dimension reduction, and generating an age characteristic model. In addition, the invention also provides the age characteristic model generated through the above method, and an Asian human face age estimation method. The age characteristic model carries out the extraction of the features based on a human face important organ region and a human face wrinkle region, and guarantees that the features comprise the sufficient information sensitive to the age estimation. The age estimation method can obtain a more precise age estimation value, and meets the demands of an actual application scene.

Description

technical field [0001] The invention relates to the technical fields of computer vision and machine learning, in particular to a method for generating an age characteristic model of an Asian face and an age estimation method. Background technique [0002] As an object that is very difficult for computers to recognize and analyze, human face has attracted extensive attention of researchers since the 1990s. Successful and effective face age estimation has great application prospects in the fields of intelligent monitoring, video indexing, and demographic information statistics. The mean absolute error of face age estimation is its key indicator. [0003] Compared with problems such as face gender recognition or facial expression recognition, the problem of face age estimation itself is a complex and difficult problem. Even if it is judged by human eyes, it is difficult to accurately estimate a person's age based on facial information alone. , while the human eye can easily j...

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Problems solved by technology

This is because researchers in this field use foreign public data sets in the process of method design, feature extraction, testing, etc., and these data sets are composed of European and American face data; therefore, the methods proposed based on these public data sets It is very effective in age estimation of European and American faces, but when used in the analysis of Asian faces, the effect will drop significantly

Moreover, the face contours of Europeans and Americans are generally larger than those of Asians, and Asian faces have more local subtle changes, that is, more information in local areas, so existing methods cannot capture and describe them well. these messages

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