Face image non-negative feature representation and recognition method and system based on conjugate gradient method, and storage medium

A conjugate gradient method and face image technology, applied in the field of data processing, can solve problems such as slow convergence speed, and achieve the effect of speeding up the convergence speed

Active Publication Date: 2019-07-30
SHENZHEN UNIV
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Problems solved by technology

[0018]1. Traditional non-negative matrix factorization (AccMU-NMF) based on multiplicative iterative algorithm and non-negative matrix factorization (AccMU-NMF) based on accelerated multiplicative iterative algorithm ) are constructed based on the gradient descent method, resulting in slower convergence

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  • Face image non-negative feature representation and recognition method and system based on conjugate gradient method, and storage medium
  • Face image non-negative feature representation and recognition method and system based on conjugate gradient method, and storage medium
  • Face image non-negative feature representation and recognition method and system based on conjugate gradient method, and storage medium

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Embodiment Construction

[0060] The present invention mainly meets the requirement of non-negativity by restricting the step size in the iterative update formula. This not only retains the properties of the conjugate gradient method itself, but also makes the decomposition have a faster convergence speed. We theoretically prove the convergence of the algorithm through an ingenious method, and verify the effectiveness of the algorithm through experiments. Experiments on public face data show that our algorithm has a better face recognition effect.

[0061] The main purpose of the present invention has:

[0062] 1. A new conjugate gradient algorithm is proposed to replace the gradient descent method as an optimization algorithm for non-negative matrix factorization, which ensures non-negativity by limiting the step size of each update.

[0063] 2. Based on the conjugate gradient algorithm, a new face recognition method with high recognition performance and convergence speed is developed.

[0064] 1. ...

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Abstract

The invention provides a face image non-negative feature representation and recognition method and system based on a conjugate gradient method, and a storage medium. The face image non-negative feature representation and recognition method comprises the steps of 1, converting a training sample image into a training sample matrix, setting an error threshold and a maximum number of iterations, and inputting the training sample matrix, the error threshold and the maximum number of iterations into the training sample matrix; 2, initializing the base image matrix and the coefficient matrix; 3, updating the base image matrix and the coefficient matrix according to a formula (7); and 4, judging whether the objective function or the number n of iterations reaches the maximum number of iterations,if yes, outputting the base image matrix and the coefficient matrix, and if not, executing the step 3. The method disclosed by the invention has the beneficial effects that the result shows that the method developed by the invention has a certain superiority through experimental comparison with a related algorithm in a disclosed face database.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a non-negative feature representation and recognition method, system and storage medium of a face image based on a conjugate gradient method. Background technique [0002] With the advent of the information age, biometrics, which uses the inherent physiological and behavioral characteristics of the human body for personal identification, has become one of the most active research fields. Among the many branches of biometric technology, the most easily accepted technology is face recognition technology, because compared with other biometric technologies, face recognition is non-invasive, non-mandatory, and non-contact. and concurrency. [0003] Face recognition technology consists of two stages. The first stage is feature extraction, which is to extract the face feature information in the face image. This stage directly determines the quality of face recognition technolog...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/16G06F18/2133G06F18/214Y02T10/40
Inventor 陈文胜陈海涛
Owner SHENZHEN UNIV
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