Three-dimensional transformation search method for extracting characteristic points in human face image

A technology of feature point extraction and three-dimensional transformation, applied in the field of face recognition, which can solve problems such as inability to fully reflect changes in face poses, poor results, and differences

Inactive Publication Date: 2009-08-05
广州衡必康信息科技有限公司
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Problems solved by technology

This method has a good effect in the general frontal face positioning, but the effect is not good for the face positioning with a certain angle deflection
Through analysis and experiments, we found that this is related to the image search method: the current ASM method is to approximate the releva

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  • Three-dimensional transformation search method for extracting characteristic points in human face image
  • Three-dimensional transformation search method for extracting characteristic points in human face image
  • Three-dimensional transformation search method for extracting characteristic points in human face image

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Embodiment Construction

[0074] The flow chart of the face three-dimensional transformation search method of the present invention is as figure 1 As shown, people's head and facial organs all have similarity aspect shape and position, according to this, can construct a standard three-dimensional human face model; coordinates, and then perform three-dimensional transformation ASM shape search based on three-dimensional coordinates; since the actual search is a two-dimensional image, it needs to be projected to a two-dimensional plane at last, and the process of three-dimensional search transformation is as follows:

[0075] First, construct a standard 3D model of the face (x 1 ,y 1 ,z 1 , x 2 ,y 2 ,z 2 ,...,x n ,y n ,z n ) (wherein the front of the face is the XY plane), the feature points in the 3D model should include the feature points in the actual 2D image (in order to reflect the adaptability of the standard 3D model, it can be more than the feature points in the actual 2D image).

[00...

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Abstract

The invention discloses a three-dimension transform search method for extracting characteristic point in face image which uses ASM (Active Shape Models) method locating face image as a base, changes two-dimension transform shape search method in present ASM into three-dimension transform shape search method. The method includes steps as follows: firstly, constructing a standard face three-dimension model; secondly, constructing three-dimension coordinates of a two-dimension stat model (basic shape) of ASM train centralizing face characteristic point according with standard face three-dimension model; finally, processing three-dimension transform to the two-dimension stat model having three-dimension coordinate and projecting to the two-dimension plane for approaching the given face characteristic point shape after search, wherein the search process adopts the method of two-step conversion and iterated approximation. The method can reflect real change of face gesture and has more search precision; the test result shows: the method can more approach fact characteristic point compared with present two-dimension transform search method.

Description

technical field [0001] The invention belongs to the field of face recognition, and in particular relates to a method for extracting feature points of facial organs of a face. Background technique [0002] Face recognition is a biometric identification technology based on human facial feature information, in which facial feature point extraction is the basis for face recognition. Face recognition as a way of identifying people has broad application prospects. At present, although some commercial face recognition systems are gradually entering the market, these technologies and systems are far from being practical, and their performance and accuracy are yet to come. improve. At present, the ASM (Active Shape Models, active shape model) positioning method is commonly used in face feature point extraction, which generally includes three steps: (1) obtain a real shape description by aligning training sample sets; (2) capture Statistics of aligned shapes; (3) Search for shape in...

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Application Information

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IPC IPC(8): G06K9/00G06K9/46
Inventor 易法令
Owner 广州衡必康信息科技有限公司
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