Facial image identification method based on word bag model

A face image and recognition method technology, applied in the field of face image recognition, can solve the problems of long time, long running time and consumption of the recognition process, and achieve the effect of shortening time, shortening running time and accurate visual dictionary

Active Publication Date: 2014-04-23
HARBIN ENG UNIV
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AI Technical Summary

Problems solved by technology

However, due to the sharp increase in the number of feature points obtained by intensive extraction and the increase in the number of image

Method used

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  • Facial image identification method based on word bag model
  • Facial image identification method based on word bag model
  • Facial image identification method based on word bag model

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Experimental program
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Embodiment Construction

[0036] Such as figure 1 , figure 2 as shown,

[0037] Step 1: Extract the face image in the database, divide the face image into 5×5 regions, and then perform dense feature extraction on each region to obtain a series of feature vectors;

[0038] The Dense-SIFT algorithm is used for uniform sampling, and image features are extracted at 2-pixel intervals, and the size of each sampling grid corresponds to different databases. Different scale parameters will be set, and each feature point extracted is 128-dimensional. vector, so each region gets a set of feature vectors.

[0039] Step 2: Use the binary K-means clustering algorithm to cluster the feature vectors representing each region, generate a visual dictionary, match the feature vectors with the visual dictionary, generate a histogram of the corresponding region, and then use a face image with visual word histogram to represent;

[0040] Generate a visual dictionary by the following method,

[0041] Step 2.1: Treat a g...

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Abstract

The invention relates to a facial image identification method based on a word bag model. The facial image identification method comprises the following steps: 1, extracting a facial image in a database, partitioning the facial image into 5*5 areas, and performing dense feature extraction on each area to obtain a series of feature vectors; 2, clustering the feature vectors representing each area by using a binary K mean clustering algorithm to generate a visual dictionary, matching the feature vectors with the visual dictionary to generate a histogram of a corresponding area, and expressing the facial image with the visual word histogram; 3, inputting the visual word histogram representing each facial image into a classifier, training and clustering to obtain an identification result.

Description

technical field [0001] The invention relates to a face image recognition method. Background technique [0002] Computer face recognition technology is a technology that uses computers to analyze face images, and then extract effective identification information from them to "identify" identities. Due to various potential applications in the fields of national public security, information security and human-computer interaction, face recognition has become a research focus in the field of pattern recognition research, and has attracted extensive attention from experts and scholars from various countries. In the past two decades, a lot of research work on face recognition has been carried out, and a large number of recognition methods have also been produced. The overall matching method represented by Principal component analysis (PCA), linear discriminant analysis (LDA) and independent component analysis (ICA) and Elastic Bunch Graph Matching (EBGM), Active Shape Model (ASM)...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
Inventor 赵春晖李晓翠苍岩王桐陈春雨
Owner HARBIN ENG UNIV
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