Method and device for positioning human face features

Abstract

The invention provides a method and a device for positioning human face features. The corresponding method comprises the following steps of: acquiring initial human face shapes through a preset human face detection algorithm, wherein the initial human face shapes comprise the width and the length of human faces and the central positions of the human faces; searching the initial human face shapes through decision functions to acquire human face feature points; determining whether the human face feature points are accurately positioned or not through algorithms of preset iterations and preset convergence probability; searching the initial human face shapes again through the decision functions if the human face feature points are not accurately positioned; and outputting the positioned human face feature points if the human face feature points are accurately positioned. According to the method and the device, the human face feature points are judged through the iteration algorithm and the convergence probability, so that whether the human face feature points are accurately acquired or not is determined, the human face features can jump out of the algorithm and are reacquired when not accurate, the searching time and the calculated amount can be reduced, and the identification accuracy of the human face feature points is further improved.

Description

technical field [0001] The invention relates to a face feature positioning method and device, belonging to the technical field of face feature positioning. Background technique [0002] Facial feature point location is a technology in which a computer or other device first performs face detection in a given picture or video, and obtains key feature points of the face. [0003] The existing facial feature point detection methods mainly include: methods based on gray information, methods based on prior rules, methods based on statistics, methods based on wavelet and wavelet packets, methods based on geometric shapes, etc. Among them, the method based on grayscale information is an effective method for extracting image features based on grayscale information, but it is easy to fail when the pose changes greatly or the background is complex; the method based on prior rules is generally about facial features. The empirical description of the characteristics makes this kind of me...

AI Technical Summary

Problems solved by technology

[0004] The present invention aims to solve the problems of low recognition accuracy of face feature points existing in the existing face feature point positioning, long s

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