Method and device for positioning key feature point

Abstract

The invention discloses a method for positioning a key feature point, which comprises the following steps: detecting a face in a target image and determining the face area in the target image as an image to be aligned; extracting the edge information in the image to be aligned to obtain an edge graph of the image to be aligned; detecting all candidate feature points from the edge graph according to a pre-set feature point selecting standard; and selecting a plurality of candidate feature points with the highest match degree with a set reference feature point from the candidate feature points to serve as the finally obtained key feature points. The invention further discloses a device for positioning the key feature point, which comprises an image to be aligned determining module, an edge graph acquiring module, a candidate point determining module and a key feature point determining module. The method and device of the embodiment of the invention can accurately position the key feature point in the face area, and the algorithm of the scheme has the advantages of simplicity, small calculation amount and fast implementation.

Description

technical field [0001] The invention relates to image recognition and processing technology, in particular to a method and device for locating key feature points. Background technique [0002] With the rapid development of current computer technology, computer processing capabilities have been greatly improved; at the same time, related technologies in the fields of pattern recognition and computer vision have also achieved rapid development. Face detection is a hot spot in research and application in related fields. , has important practical value and has been widely used in many fields such as security, entertainment, and human-computer interaction. [0003] Face detection refers to the use of face detection, facial feature point positioning and other technologies to obtain the face position information in the image, and based on the face position information, a certain algorithm is used to extract the information contained in the face image. method. At present, with the...

AI Technical Summary

Problems solved by technology

[0004] In order to extract the key feature points on the face, the early methods include the method based on the geometric features of the face and the method based on Adaboost. These methods are mainly based on the distribution of a single key feature point when matching key feature points. , it is prone to positioning deviation, so it is often only possible to find approximate key point positions, and the final selected key point positions are not very accurate—for example, the eyeball point can be positioned to the eyebrow, and the corner of the eye point may be positioned to the eyeball point, etc.; at the same time, all The robustness of the above method is poor, and it is sensitive to the influence of light; therefore, the stability and reliability of feature point positioning are not high; in addition, there is a method based on elastic template, which has a better positioning effect. However, due to the complexity of the algorithm, the processing time required to determine the final key feature points is usually longer, so the algorithm can only be used when the real-time requirements are not high, and the application range is relatively limited.

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