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Method used for designing large-quantity face recognition search engine and based on Hadoop cloud computing frame

A search engine, massive human technology, applied in the field of massive face recognition search engine design, can solve the problems of poor stability, high development difficulty and difficult maintenance of massive face recognition search engines, achieve good stability, ensure real-time and Reliable, simple effect

Active Publication Date: 2013-08-07
CHONGQING UNIV
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AI Technical Summary

Problems solved by technology

[0005] In order to solve the shortcomings of high development difficulty, poor stability, and difficult maintenance of massive face recognition search engines based on cloud computing, the present invention proposes a face recognition search engine design method based on the Hadoop framework, based on the mature Hadoop cloud computing framework , to achieve stable and efficient massive face recognition

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  • Method used for designing large-quantity face recognition search engine and based on Hadoop cloud computing frame
  • Method used for designing large-quantity face recognition search engine and based on Hadoop cloud computing frame
  • Method used for designing large-quantity face recognition search engine and based on Hadoop cloud computing frame

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Embodiment Construction

[0017] The implementation manner of the present invention will be further described below in conjunction with the flowchart and examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0018] Such as figure 1 Shown is the architecture diagram of the face recognition search engine proposed by the present invention. The search engine consists of three layers: inner layer, middle layer and outer layer. Among them, the inner layer is composed of face identity information data table and face feature vector distributed comparison computing node 1, computing node 2, computing node 3 ... computing node M; the middle layer is composed of face feature vector clustering index table and several Cluster list table data sets 1, 2, 3...n, each data set corresponds to 1-dimensional features; the outer layer is composed of human-computer interaction query interface and face feature vec...

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Abstract

A method used for designing a large-quantity face recognition search engine and based on a Hadoop cloud computing frame belongs to the field of cloud computing and mode recognition. Based on the Hadoop cloud computing frame, the search engineis formed by an inner layer, a middle layer and an outer layer. The inner layer is used for storing a large quantity of face images and identity information and providing distributed computing resources. The middle layer is used for building and maintaining an index table of the search engine, and the outer layer is used for receiving tasks and distributing tasks. In order to increase searching speed of the face images in a data base while the precision is guaranteed, a K-means clustering algorithm is used in the middle layer to build a face feature vector cluster index table to be combined with a clustering list table. By means of the method, cheap common server groups can be used for building the large-quantity face recognition search engine, and the method is achieved based on the Hadoop cloud computing frame proved by a large amount of practice, has good stability and is simple and easy to implement.

Description

technical field [0001] The invention belongs to the field of cloud computing and pattern recognition, and in particular relates to a design method of a massive face recognition search engine based on Hadoop cloud computing framework. Background technique [0002] In modern society, video surveillance is the main monitoring system to realize social public security prevention and control. The video information collection points all over the city gather massive video information to the monitoring center, providing massive information for the city's public security prevention and control. However, due to the lack of intelligent mass video analysis technology, the utilization rate of this information is extremely low. In order to make full use of this information and ensure social security, people try to apply face recognition technology to intelligent video analysis to quickly confirm the identity of criminal suspects. However, in the face of massive face image information, th...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06K9/00
Inventor 杨利平李力龚卫国李伟红李正浩王立
Owner CHONGQING UNIV
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