Age estimation method and system based on multi-scale linear difference texture features

Abstract

The present invention discloses a method and system for age estimation based on multi-scale linear difference texture features, wherein the method includes: first, using Haar-like features and Adaboost classifier algorithm to detect the human face in the picture to be tested, and Cut out the face area; then extract texture features based on multi-scale linear difference features in the cut out face area, and use a decision tree for feature selection to reduce the dimension of the feature vector; finally, the feature after reducing the dimension of the feature vector Train the SVR model in space, and use the SVR model to predict the age of face pictures. Age estimation is performed due to the adoption of non-linear support vector regression based on RBF kernel as the classifier model. Its age estimation is more accurate, and the age estimation is performed through face pictures, which can make human-computer interaction more humane and safer.

Description

technical field [0001] The invention relates to the technical field of biological identification, in particular to an age estimation method and system based on multi-scale linear difference texture features. Background technique [0002] Face pictures contain rich personal information, including identity, age, gender, and race, which are widely used in the field of human-computer interaction. With the development of e-commerce and the popularization of various mobile devices, user's age information plays an increasingly important role in human-computer interaction. Age estimation based on face pictures has broad application prospects in human-computer interaction, such as security monitoring, user management in e-commerce, website access control, image and video retrieval, and more humanized human-computer interaction functions. [0003] Relying on the biometric feature of the face for age estimation does not require active cooperation from the user, so the operation is hig...

AI Technical Summary

Problems solved by technology

[0004] However, in the existing human-computer interaction process, the judgment of the user's age has problems such as difficult identification or large judgment errors.

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