Posture recognition method of human's face based on limited Boltzmann machine neural network

A limited Boltzmann machine and limited Boltzmann machine technology, applied in the field of image recognition, can solve the problems of data innuendo, limited application, and cannot be directly applied to face gesture recognition, etc., to reduce the error rate and calculate the speed. Fast, easy-to-achieve effects
CN1952953AInactive Publication Date: 2007-04-25SHANGHAI JIAO TONG UNIV
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
SHANGHAI JIAO TONG UNIV
Publication Date
2007-04-25
Estimated Expiration
Not applicable · inactive patent

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Abstract

This invention relates to Boltzman neutral network for human face identification method in image identification technique field, which comprises the following steps: a, pre-processing human images training samples with different positions; b, initiating limited Boltzman neutral network; c, pre-training limited Boltzman neutral network; d, adjusting limited Boltzman neutral network parameters; e, identifying new human face position. This invention relates to human face testing, mode sorting, human face position identification for re-establish three dimensional human faces and identification.
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Description

technical field

[0001] The invention relates to a method in the technical field of image recognition, in particular to a method for face gesture recognition using a restricted Boltzmann machine neural network. Background technique

[0002] With the strengthening of global security awareness, human beings have higher and higher requirements for biometric identification technology, and among many biometric identification technologies, face recognition is the most feasible. However, the traditional two-dimensional face recognition is affected by factors such as illumination and posture, which cannot meet the requirements of practical applications. Therefore, it is a trend to expand from two-dimensional face recognition to three-dimensional face recognition, because three-dimensional space can provide more information for face recognition. However, this expansion from two-dimensional recognition to three-dimensional recognition also brings new problems, that is, how to estimate...

Claims

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