A face key point positioning method with shielding robustness

Abstract

The invention discloses a shielding robust face key point positioning method, and belongs to the field of face key point positioning. The method comprises the following steps of S1, collecting face images marked by key points as a training data set and a test data set; S2, for the training data set and the test data set in the step S1, firstly carrying out face detection and five-point key point positioning by using a face detection algorithm MTCNN, and then converting a face by using Procrustes analysis transformation T to obtain a corrected face sample so as to form a training sample and a test sample; taking the corrected face sample as the input of the S3 stage; S3, learning the training sample in the step S2 through a convolutional network; and S4, after the convolutional network completes the training in the step S3, inputting the test sample in the step S2 into the convolutional network, and obtaining the positions of the face key points in the image. The method has robustness for face key point positioning under the shielding condition, and the test result and the qualitative positioning result of the corresponding picture also prove the effectiveness of the method.

Description

technical field [0001] The invention belongs to the field of human face key point positioning, and in particular relates to an occlusion robust human face key point positioning method. Background technique [0002] Face key point positioning technology is based on face images. First, it detects whether there is a face on the input face image or video stream. If there is a face, it further gives the position of each face and the position of key points, such as The location of the major facial organs such as the nose, eyes, and mouth. This technology can be used for face pose correction, pose recognition, fatigue monitoring, 3D face reconstruction, face animation, face recognition, expression analysis, etc. Wrong key point positioning will lead to face distortion and deformation, so an algorithm that can accurately extract face key points is very important. The whole process includes face detection, face preprocessing, face key point positioning and other modules. [0003] ...

AI Technical Summary

Problems solved by technology

[0008] Although there are many relatively mature algorithms for face key point positioning under medium posture, there is still a relatively large room for improvement in face key point positioning under occlusion.

Images