Similarity calculation method and similarity calculation system in face recognition

Abstract

Embodiments of the invention disclose a similarity calculation method and a similarity calculation system in face recognition. The method comprises the following steps: acquiring a target image of a target face and N to-be-compared images of a first to-be-compared face; based on the target image, the N to-be-compared images and a pre-stored face feature extraction model, converting the target image into a target feature vector, and converting the N to-be-compared images into N to-be-compared feature vectors; calculating the distance measure of the target feature vector and a to-be-compared feature vector set, wherein the to-be-compared feature vector set is composed of the N to-be-compared feature vectors; and determining the similarity between the target face and the first to-be-compared face based on the pre-stored mapping relationship between distance measure and similarity and the calculated distance measure. The embodiments of the invention further disclose a corresponding similarity calculation system in face recognition. By using the technical scheme provided by the embodiments of the invention, the accuracy of face recognition can be improved.

Description

technical field [0001] The invention relates to the technical field of face recognition, in particular to a similarity calculation method and system in face recognition. Background technique [0002] The essence of the existing face recognition technology is to calculate the similarity between two face images. If the similarity between the two faces is greater than a preset threshold, the two faces are the same person. In practical applications, such as identity verification (judging whether the target face image is the same person as the corresponding image in the identity database), face deployment control (judging whether the target face image is a person in the key personnel database), face search (judging Whether there is a face image matching the target face image in the portrait database), there are often multiple face images of a person for comparison and insertion. The existing technology compares the target face image with multiple face images of the person one by...

AI Technical Summary

Problems solved by technology

[0003] The problem with the above method is that if the similarity results corresponding to multiple face images are not high enough, the existing technology may mistakenly determine that the target face image is not the same person as the person, and judge that the target face image is not the same person as another person. The same person, resulting in a decrease in the accuracy of face recognition

Images