Method for making human face posture estimation utilizing dimension reduction method

A face pose and dimensionality reduction technology, applied in the field of image recognition, can solve the problems of increased computing time, increased training time, slow speed, etc., to achieve the effect of reducing training time, improving testing speed, and reducing the number of nodes

Inactive Publication Date: 2007-08-22
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

However, the training time of this method increases sharply with the number of training samples and the number of dimensions.
However, in practical applications, the face image is disturbed by the outside world during the generation process and contains a lot of redundant information and noise. These redundant information and noise will not only increase the calculatio...

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  • Method for making human face posture estimation utilizing dimension reduction method
  • Method for making human face posture estimation utilizing dimension reduction method
  • Method for making human face posture estimation utilizing dimension reduction method

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Embodiment

[0026] 1. the face bank (this face storehouse contains the face images of 9 different attitudes of 2270 people. As shown in Figure 1, figure a, b, c, d, e, f, g, h, i these The poses of the 9 face images are -90°, -60°, -45°, -30°, 0°, 30°, 45°, 60°, and 90°. poses are divided into 9 categories, each category has 2270.) All images in the scale are 30 pixels high and 30 pixels wide, and then the scaled face image is transformed into a grayscale image, and Normalize the pixel gray value of the image to [0, 1], and finally pull the gray image into a vector with a length of 900.

[0027] 2. Perform PCA processing on all the vector data in step (1), keep 98% of the information, and finally reduce the dimension of the vector from 900 dimensions to 342 dimensions, and obtain the average vector And the feature vector P, if the original 900-dimensional vector data is expressed as X, and the dimensionally reduced 342-dimensional data is expressed as b, then X can be expressed as: ...

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Abstract

This invention discloses a method for estimating man-face gestures by a dimensionality reduction method including the following steps: 1, preprocessing man-face image trained samples of different gestures, 2, carrying out PCA process to processed data, 3, initializing limited nerve network of a Boltzmann machine, 4, pre-training the limited Boltzmann machine nerve network with the data processed by PCA, 5, adjusting the limited Boltzmqnn nerve network parameters, 6, identifying gestures of new man-face images, which reduces the error rate even further compared with the present technology and reduces its dimensions greatly.

Description

technical field [0001] The invention relates to a method in the technical field of image recognition, in particular to a method for estimating face posture by combining principal component analysis (PCA) and a dimensionality reduction method of a restricted Boltzmann machine neural network. Background technique [0002] At present, the research focus of face recognition has been extended from 2D to 3D, and the core technology in 3D face recognition is how to estimate the 3D pose of the face based on the 2D face image. Pose estimation is essentially a classification problem, that is, to judge which pose a face in a face image belongs to. However, face images are typical high-dimensional data, and general classification methods cannot be directly applied to pose estimation. Therefore, it is necessary to reduce the dimensionality of high-dimensional face data first, and then perform pose estimation on the reduced-dimensional data. [0003] Through the retrieval of prior art do...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
Inventor 杨杰杜春华张田昊署光杨晓超
Owner SHANGHAI JIAO TONG UNIV
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