Hybrid Fusion Face Recognition Method Based on Ensemble Learning

Abstract

The invention discloses a fused face recognition method based on integrated learning, which comprises the following steps: 1.) inputting a face image to be identified; 2.) identification based on ART2 (Adaptive Resonance Theory 2) face recognition method: if the ART2 network system has a returned recognition result, receiving the recognition result, which means the identification is successful, else, entering the next step; 3.) identification based on feature face recognition method: assuming that the threshold of the method is S and the identification score of the face image by the method iss, if s>S, receiving the recognition result, which means that the identification is successful, else, entering the subsequent fused identification step; and 4.) fused identification: sequencing by using the degrees of similarity which are respectively given out by the two single recognition methods, and comparing the recognition results, wherein the first ones in the sequence are identical, receiving the recognition result, which means that the identification is successful, else, the identification fails. By adopting the concept of integrated learning, the ART2 face recognition method and feature face recognition method are fused and complemented, thereby overcoming the limitations in the single face recognition method and enhancing the integral recognition performance.

Description

technical field [0001] The invention relates to the technical field of automatic face recognition, in particular to a method for hybrid fusion face recognition based on integrated learning. Background technique [0002] Face recognition technology is based on human facial features. For the input face image or video stream, it first judges whether there is a human face in it. If there is a human face, it further gives information such as the position and size of each face. Based on this information, the identity features contained in each face are further extracted, and compared with known faces, so as to identify the identity of each face. [0003] The advantage of face recognition lies in its naturalness and the characteristics of not being noticed by the individual being tested. The so-called naturalness means that the identification method is the same as the biological characteristics used by human beings to identify individuals. For example, face recognition, human bei...

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is to adopt the idea of ​​ensemble learning, provide a hybrid fusion face recognition method based on ensemble learning, integrate and complement the face recognition method based on ART2 and the eigenface recognition method, and overcome the single human face recognition method. Limitations of face recognition methods to improve overall recognition performance

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