Face detection method based on child cross-age group face recognition technology

Abstract

The invention relates to a face detection method, in particular to a face detection method based on a child cross-age face recognition technology, which comprises the following steps: acquiring a training face database and an age face database, extracting face basic features in the training face database, and inputting the face basic features into a double-layer heterogeneous deep neural network for training; and extracting face features of the same person at different ages and ages corresponding to the face features in the age face database, inputting the face features and the ages corresponding to the face features into a double-layer heterogeneous deep neural network for training to obtain a spatial mapping relationship of the face features at different ages, and processing at least twodifferent to-be-recognized face images to obtain a face recognition result; inputting the to-be-recognized face image into the trained double-layer heterogeneous deep neural network, and judging whether the face images are the same person or not by the double-layer heterogeneous deep neural network according to the similarity of the face features extracted from the to-be-recognized face image; according to the technical scheme provided by the invention, the defect that the cross-age face cannot be quickly and effectively recognized in the prior art can be effectively overcome.

Description

technical field [0001] The invention relates to a face detection method, in particular to a face detection method based on children's face recognition technology across age groups. Background technique [0002] As an important biometric identification technology, face recognition has become a research hotspot in the fields of image processing and pattern recognition, and has also been widely used in public security, human-computer interaction and identity authentication. [0003] In the practical application of face recognition, the face image to be recognized is affected by various factors, among which the change of the face image due to age changes is particularly prominent. Although the accuracy of general face recognition has been improved with the development of deep learning technology, face recognition across ages is still very challenging. Nevertheless, due to its irreplaceable value in many scenarios, such as finding lost children, long-term wanted criminals, face ...

AI Technical Summary

Problems solved by technology

[0007] Aiming at the above-mentioned shortcomings in the prior art, the present invention provides a face detection method based on children's cross-age face recognition technology, which can effectively overcome the inability to quickly and effectively recognize cross-age faces in the prior art Defects

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