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Multi-feature fusion identification algorithm used for human face comparison

A multi-feature fusion and recognition algorithm technology, applied in the field of multi-feature fusion recognition algorithms, can solve the problems of poor actual combat effect and low accuracy of single algorithm comparison, and achieve the effect of rapid integration

Active Publication Date: 2017-05-10
河北三川科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0008] The purpose of the present invention is to provide a method for recording the results of each calculation and operation, counting the actual combat effects, and adjusting the weights of various algorithms according to the effects, so as to realize the unified scheduling and cooperative operation of various algorithms, and make full use of various algorithms. A multi-feature fusion recognition algorithm for face comparison that solves the problems of low accuracy of single algorithm comparison and poor actual combat effect

Method used

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  • Multi-feature fusion identification algorithm used for human face comparison
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  • Multi-feature fusion identification algorithm used for human face comparison

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Embodiment 1

[0042] Such as figure 1As shown, a multi-feature fusion recognition algorithm for face comparison includes a template database and a learning sample library. The template database can configure one or more algorithms for different business modules to model, compare, and identify applications. ; Set the algorithm weight, score and result combination rules separately to obtain the final recognition score and store it in the learning sample library;

[0043] The learning sample library conducts statistical learning for the hits of the training sample library and the actual application comparison results, and dynamically adjusts the weights of each algorithm; finally, according to the result merging rules, the recognition results of various algorithms are deduplicated, sorted, and classified; the template database includes face Data collection module, face feature collection module, face feature recognition algorithm module, face recognition score module, multi-classifier fusion m...

Embodiment 2

[0056] Such as figure 1 As shown, a multi-feature fusion recognition algorithm for face comparison includes a template database and a learning sample library. The template database can configure one or more algorithms for different business modules to model, compare, and identify applications. ; Set the algorithm weight, score and result combination rules separately to obtain the final recognition score and store it in the learning sample library;

[0057] The learning sample library conducts statistical learning for the hits of the training sample library and the actual application comparison results, and dynamically adjusts the weights of each algorithm; finally, according to the result merging rules, the recognition results of various algorithms are deduplicated, sorted, and classified; the template database includes face Data collection module, face feature collection module, face feature recognition algorithm module, face recognition score module, multi-classifier fusion ...

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Abstract

The invention discloses a multi-feature fusion identification algorithm used for human face comparison, which relates to the human face recognition computer technology research and is used for solving the problems of low accuracy and poor actual application effect caused by an existing portrait identification system which does not form a learning sample library and does not change and adjust an actual application weight of an algorithm. The multi-feature fusion identification algorithm comprises a template database and the learning sample library; the template database configures one or more algorithms for different business modules to perform modeling, comparison and application capability identification; algorithm weights, scores and result combination rules are set, and a final identification score is obtained and stored in the learning sample library; and the learning sample library performs statistical learning for a training sample library and hit of an actual application comparison result, and dynamically adjusts the algorithm weights. By recording an application result of each calculation, the actual application effect is subjected to statistics, and application weights of various algorithms are adjusted according to the effect, so that unified scheduling and cooperative running of the various algorithms can be realized and the advantages of the various algorithms can be exerted.

Description

technical field [0001] The present invention relates to the research on computer technology of face recognition, in particular, it is a multi-feature fusion recognition algorithm for face comparison. Background technique [0002] The face recognition system takes portrait recognition technology as the core, is an emerging biometric technology, and is a high-tech technology in the international scientific and technological field. Human faces are very popular because they cannot be copied, are easy to collect, and do not require the cooperation of the person being photographed. The portrait recognition system has a wide range of applications: portrait recognition access management system, portrait recognition access control and attendance system, portrait recognition monitoring management, portrait recognition computer security protection, portrait recognition photo search, portrait recognition anti-registration, etc. [0003] China Dissertation Abstracts Database, author Che...

Claims

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Application Information

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IPC IPC(8): G06K9/00
CPCG06V40/166G06V40/168G06V40/172
Inventor 王飞张宁宁王彦芳
Owner 河北三川科技有限公司
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