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

A linear difference and texture feature technology, applied in the field of biometrics, can solve the problem of difficulty in identifying and judging the user's age, and achieve the effect of accurate age estimation and human-computer interaction.

Active Publication Date: 2020-03-31
KONKA GROUP
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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.

Method used

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

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Embodiment Construction

[0047] The present invention provides an age estimation method and system based on multi-scale linear difference texture features. In order to make the purpose, technical solution and effect of the present invention clearer and clearer, the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0048] see figure 1 , which is a flow chart of the age estimation method based on multi-scale linear difference texture features of the present invention. As shown in the figure, the method includes the following steps:

[0049] S100, using the Haar-like feature and Adaboost classifier algorithm to detect the face in the picture to be tested, and cut out the face area;

[0050] S200. Extracting texture features based on multi-scale linear difference features in the clipp...

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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...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/171G06V40/178G06F18/2148G06F18/2411
Inventor 杨卫国张嘉奇郭振华杨余久王序
Owner KONKA GROUP
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