A Face Retrieval Method Based on Multi-task Convolutional Neural Network

Abstract

The invention discloses a face retrieval method based on a multi-task convolutional neural network, comprising steps: for any face image, detecting and obtaining the position of the face and the position of key points; performing a preprocessing operation on the face image; The multi-task convolutional neural network is pre-established, and then trained; the pre-processed face image is input into the multi-task convolutional neural network that has completed the training; the face feature database is pre-established; the face image is Calculate the identity feature similarity with the face feature database to obtain a list of candidate face images; calculate the similarity of multiple attribute feature expression vectors between the face image and the candidate face image; normalize and fuse; score according to the fusion similarity Sort to get search results. The invention can ensure high-quality recognition of human face images, quickly and effectively carry out corresponding user identity recognition and judgment on a large number of human face images, and meet people's requirements for face recognition functions.

Description

technical field [0001] The invention relates to the technical fields of artificial intelligence, pattern recognition and digital image processing, and in particular to a face retrieval method based on a multi-task convolutional neural network. Background technique [0002] At present, with the continuous development of human science and technology, face recognition technology is becoming more and more popular in people's daily life. No matter in artificial intelligence research or public security applications, face recognition technology has always been a cutting-edge and popular technology. status. [0003] As a type of biometric identification technology, face recognition has a good development and application prospect due to its non-contact and convenient collection characteristics. Face recognition technology has played a very important role in many application scenarios, such as airport security check, border inspection and customs clearance. In recent years, with the...

AI Technical Summary

Problems solved by technology

[0005] However, with the advent of the era of big data, the scale of data that people need to process is often very large

As the capacity of the database increases, the possibility of similar faces appearing in the database will increase accordingly. When face recognition is performed based on the existing face recognition methods, the probability of misidentification will be greatly increased as the faces are verified one by one. increase, unable to meet people's fast and accurate recognition requirements for face recognition, and the overall work efficiency and quality of face recognition are low, which reduces people's experience

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