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Method for extracting face features

A technology of facial features and extraction methods, applied in the field of image analysis

Active Publication Date: 2013-01-16
NINGBO UNIV
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Problems solved by technology

Based on the foregoing in this paragraph, although Kinect cameras have been widely used in human body posture analysis and recognition, and can accurately track and segment facial images under complex background and human posture conditions, so far, no human body posture analysis data provided by Kinect cameras has been used. and depth data to locate the face features, that is, there is no method of using the human body posture analysis data and depth data provided by the Kinect camera to extract face features

Method used

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  • Method for extracting face features
  • Method for extracting face features

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Embodiment Construction

[0027] The present invention will be further described below in conjunction with specific examples.

[0028] image 3 It is a position map of 68 marker points of the face of the present invention. The numbers on the overlapped part of the mouth are 60, 61, 62, 63, 64, 65 counterclockwise, and the number 66 is on the center of the mouth.

[0029] A kind of face feature extraction method that the present invention proposes is based on the Depth-AAM algorithm, and the Depth-AAM algorithm belongs to the improvement of the face feature positioning algorithm of two-dimensional images—the AAM algorithm, and makes full use of the human body posture analysis provided by the Kinect camera Data and depth data, they are fused into the AAM algorithm to form a face feature positioning method based on 2.5-dimensional images.

[0030] Described human face feature extraction method, comprises the following steps,

[0031] 1) Use the principal component analysis method to train the appearanc...

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Abstract

The invention discloses a method for extracting face feature. Accordingly, body posture analytical data and depth data provided by a Kinect camera are combined with a Depth-Active Appearance Model (AMM) algorithm, and the method based on 2.5 dimensional images is formed. The method comprises steps of training the AMM of the Depth-AMM algorithm by using a principal component analysis method and extracting face features based on the AMM of the Depth-AMM algorithm after completed training.

Description

technical field [0001] The invention relates to the technical field of image analysis, in particular to a face feature extraction method. Background technique [0002] The face feature extraction technology uses a computer to automatically locate the exact positions of the various organs of the face on a face image, including the eyes, nose, mouth, and the outer contour of the face, where all feature points need to be extracted. Face feature extraction can provide corresponding basic data for research work such as face recognition, expression and posture analysis, and face tracking. There are currently many feature extraction algorithms such as principal feature analysis (PCA), local binary pattern (LBP), linear discriminant analysis (LDA), Gabor wavelet transform, etc., which can be used to extract face features, but these methods can only be used under certain conditions ( Appropriate lighting, posture, makeup and facial expressions) can work well, and all the obtained lo...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/46
Inventor 赵杰煜金秋
Owner NINGBO UNIV
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