Facial expression feature extraction method based on point distribution model

A point distribution model and facial expression technology, applied in the field of computer science, can solve the problems of high category discrimination and unsatisfactory extraction effect, and achieve the effect of noise insensitivity

Inactive Publication Date: 2014-04-09
NANTONG UNIVERSITY
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Problems solved by technology

However, this method remains unchanged for irrelevant deformation, is not sensitive to noise, and the feature extraction effect of large category discrimination is not ideal.

Method used

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  • Facial expression feature extraction method based on point distribution model
  • Facial expression feature extraction method based on point distribution model
  • Facial expression feature extraction method based on point distribution model

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Embodiment Construction

[0040] The preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, so that the advantages and features of the present invention can be more easily understood by those skilled in the art, so as to define the protection scope of the present invention more clearly.

[0041] Such asfigure 1 As shown, by combining sensors to collect human face bones and depth image information, the PC has functions such as managing image files, displaying images, and analyzing the faces of people in the images, so as to perform predetermined calculations such as eyes, noses, mouths, and facial features. Features such as the shape and color of the face are extracted.

[0042] Combination sensor is a somatosensory peripheral developed by Microsoft for XBOX360. Its hardware integrates two cameras for depth image acquisition of the combination sensor. There is also a color camera and microphone. The combination sensor provides thre...

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Abstract

The invention discloses a facial expression feature extraction method based on a point distribution model. The method includes the specific steps of setting up the human body facial shape model through coordinates for marking human body facial image facial feature points, selecting relatively-ideal shape vectors as initial samples, enabling other vectors to correspond to the initial samples in shape till the difference between two adjacent average shape vectors is smaller than a certain value, and conducting calculation through a Gabor wavelet kernel function and conducting sampling to achieve fine mapping of the facial feature points of a set of feature points with different frequencies and phases. By means of the method, according to the facial expression feature extraction method based on the point distribution model, the elastic graph matching of human face recognition is conducted through a Gabor wavelet conversion coefficient, ideal facial expression features which are not affected by the samples are obtained, and the method has the obvious advantages for extracting features which are kept unchanged under uncorrelated deformation, insensitive to noise and high in category distinction degree.

Description

technical field [0001] The invention relates to the field of computer science, in particular to a method for extracting facial expression features based on a point distribution model. Background technique [0002] Human beings can express information through voice and body, and facial expression is the most informative part of body language. Usually, in daily activities, facial expression language is a means of communication and communication that can express meaning without sound. Way, as the carrier of information, through voice and facial expression language, it can express a lot of semantic information except voice. Facial expression automatic recognition, feature extraction and analysis of facial expression information, in order to classify based on the understanding and way of thinking and understanding, through emotional computing, computer association, thinking and reasoning, and then understand the meaning expressed by human facial information. In the field of comp...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/66
Inventor 胡传志邱建林胡晓燕仲蓓鑫程实
Owner NANTONG UNIVERSITY
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