Face identification method and device based on multiple models

Abstract

The invention discloses a face identification method and device based on multiple models. The face identification method comprises the steps of firstly dividing the sample data according to the defined classification, and generating a plurality of sample files, each of which includes a kind of sample data; secondly conducting preprocessing on the data samples of all the sample files, and detectingfaces in the sample images and conducting normalization; thirdly obtaining different models from the data sample of each sample file after preprocessing by using different training methods like different face identification algorithms or the same face identification algorithm, wherein the data sample of the same sample file corresponds to multiple models; finally adopting multiple models to conduct identification on faces to be identified, and obtaining multiple face identification results and selecting the final face identification result. The invention is advantageous in that the face identification accuracy can be increased; model training time can be reduced; with the adoption of multiple models for concurrent computing, time of searching and contrasting can be reduced.

Description

technical field [0001] The invention relates to deep learning of artificial intelligence, in particular to a multi-model-based face recognition method and device. Background technique [0002] The research on the face recognition system began in the 1960s. After the 1980s, it was improved with the development of computer technology and optical imaging technology, and it really entered the primary application stage in the late 1990s. Technology implementation is the main focus; the key to the success of the face recognition system is whether it has a cutting-edge core algorithm, and the recognition result has a practical recognition rate and recognition speed; the "face recognition system" integrates artificial intelligence, machine recognition, machine learning , model theory, expert system, video image processing and other professional technologies, and at the same time need to combine the theory and implementation of intermediate value processing. transformation. The app...

AI Technical Summary

Problems solved by technology

Each classification model is based on different features, suitable for different situations, and performs well on its features, but no one classification model can achieve optimal results on all classification problems

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