A face aging method based on principal component analysis

Abstract

The invention relates to a face portrait aging method based on principal component analysis. Firstly, photographs in an original aging photograph data set are changed from color images to gray images,then the original aging photograph data set is normalized by samples, and then the eigenvalues corresponding to each photograph are calculated by principal component analysis to obtain a photograph parameter set corresponding to the aging photograph data set. According to the age group sample, the corresponding photo parameter sets of different age groups are obtained, and the average parametersare solved. Through variance analysis of photo parameter set, the age-related eigenvalues are screened out, and then the age-related parameters in the average photo parameters of different age groupsare studied. Given the portrait to be aged, the sample is normalized first, then the normalized portrait is analyzed by principal component analysis, the corresponding eigenvalues are calculated, theage-related features are modified according to the obtained variation law, and finally the corresponding aging portrait is obtained by using principal component reconstruction strategy.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a face image aging method in the technical fields of pattern recognition and computer vision, which can be used for criminal investigation and case solving and digital entertainment. Background technique [0002] As an important branch of face aging, face portrait aging has many important practical applications, such as supporting digital entertainment and assisting the police in solving crimes. For example, aging face portraits can assist the police in finding missing children and fugitives. Due to time constraints, many sketches of lost children or fugitives need to be updated to suit the new situation. In this case, it is a good choice to update the sketch portrait through the face portrait aging algorithm. In addition, face portrait aging technology can also be used by businesses in applications such as digital entertainment. Face portrait aging can also ass...

AI Technical Summary

Problems solved by technology

The disadvantage of this method is that the aging algorithm based on muscle changes is also very complicated due to the complexity of muscle changes in the aging process of the face.

However, this method has the following disadvantages: loss of high-frequency information of faces, processing everyone in the same way, and lack of personality

The disadvantage of this method is that it is difficult for the algorithm to simulate the aging problem with a large time span because the function is simple and difficult to fit large face appearance changes

The disadvantage of this method is that it is necessary to better understand the process of face aging in order to propose reasonable evaluation criteria, and it is also a difficult problem to integrate multiple criteria.

The disadvantage of this method is: the performance of the algorithm depends on the performance of heterogeneous image conversion and face aging, and the research of heterogeneous image conversion and face aging is itself a difficult problem

[0009] In short, the face aging method based on physical model is too complex and the face aging method based on sample learning always lacks sufficient training samples

In addition, the above-mentioned face aging methods are all aimed at face photos.

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