Method and device for obtaining feature points of human face

A face feature and acquisition method technology, applied in the image field, can solve the problems of face image difficult to locate accurately, the number of convolutional neural network layers is too large, and the shape falls into a local minimum, so as to solve the problem of large amount of calculation and save calculation Resources, the effect of reducing the amount of calculation
CN107871098AActive Publication Date: 2018-04-03BEIJING EYECOOL TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
BEIJING EYECOOL TECH CO LTD
Publication Date
2018-04-03

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Abstract

The invention discloses a method and device for obtaining the feature points of a human face. The method comprises the steps: obtaining a human face after normalization processing; inputting the humanface into a convolution neural network for processing, wherein the convolution neural network comprises at least one convolution layer, at least one pooling layer, at least one local response normalization layer and at least one total connection layer, and the convolution layer is used for the convolution processing according a convolution core, the pooling layer is used for simplifying the dataof the convolution layer, and the configuration of the convolution neural network is correlated with the expected number of feature points of the human face, and is obtained through training via a predetermined training set; obtaining a plurality of feature points, processed by the convolution neural network, of the human face in the human face image. The method solves technical problems that a method for obtaining the feature points of the human face based on the convolution neural network in the prior art is large in calculation burden, and is longer in training time.
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Description

technical field

[0001] The present invention relates to the field of images, in particular to a method and device for acquiring facial feature points. Background technique

[0002] Facial feature point acquisition is to automatically locate the key feature points of the face based on the input face image. According to different application requirements, the number of key feature points is also different: the minimum is 5 feature points, including eyes, nose tip and mouth corner, which can be used for face recognition; Part of the contour points, including the contour points of the chin, that is, 68-point positioning. In face analysis tasks, it is essential to obtain facial feature points, such as face authentication and recognition, expression recognition, head pose estimation, 3D modeling of faces, and face beautification.

[0003] Facial feature point acquisition methods can be roughly divided into three categories: optimization-based methods, regression-based methods, a...

Claims

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