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Active-shape-model-algorithm-based method for analyzing face expression

An active shape model and facial expression technology, applied in the field of facial expression recognition, can solve problems such as complex process, strong technicality, and restriction of visual system efficiency

Inactive Publication Date: 2015-09-30
SUZHOU UNIV
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AI Technical Summary

Problems solved by technology

Although the research on expression recognition has made significant progress in recent years, the existing methods are generally more technical and the process is more complicated.
[0013] Traditional facial expression recognition algorithms based on image analysis need to process all pixel data of the entire image, and its algorithm complexity often restricts the efficiency of the entire visual system

Method used

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  • Active-shape-model-algorithm-based method for analyzing face expression
  • Active-shape-model-algorithm-based method for analyzing face expression
  • Active-shape-model-algorithm-based method for analyzing face expression

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Embodiment Construction

[0131] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0132] Active shape model (ASM) algorithm, also known as active contour model (Active Contour Models, ACM). This algorithm is different from other algorithms, it realizes the initiative for the first time, because it mainly minimizes the energy function through iteration, so it shows the characteristic of initiative.

[0133] The ASM algorithm is a texture modeling for the local texture of each feature point. During the search process, the local texture of the training sample is matched to locate the feature point, while the AAM algorithm is to fuse the shape and texture to create a unified appearance. The model is matched by comparing the difference between the current m...

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Abstract

The invention relates to an active-shape-model-algorithm-based method for analyzing a face expression. The method comprises: a face expression database is stored or selected and parts of or all face expressions in the face expression database are selected as training images; on the basis of the active shape model algorithm, feature point localization is carried out on the training images, wherein the feature points are ones localized based on the eyebrows, eyes, noses, and mouths of the training images and form contour data of the eyebrows, eyes, noses, and mouths; data training is carried out to obtain numerical constraint conditions of all expressions; and according to the numerical constraint conditions of all expressions, a mathematical model of the face expressions is established, and then face identification is carried out based on the mathematical model.

Description

technical field [0001] The invention relates to the technical field of facial expression recognition, in particular to a method for analyzing facial expressions based on an active shape model algorithm. Background technique [0002] The human face plays a key role in the interpersonal communication in daily life, so the research on human face and facial expression recognition has increasingly become the focus of various scholars. At the earliest, psychologists such as Ekman proposed that in the process of human daily communication, 55% of the information is transmitted through facial expressions, while the information communicated through language and sound means only accounts for 7% and 38%. A better understanding of human mental states will require an in-depth study of expressions. [0003] The research on human facial expressions originated in the 19th century. In the 1970s, Ekman and Friesen proposed a unified facial expression template, which is suitable for all human ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
Inventor 钟宝江候婕
Owner SUZHOU UNIV
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