Face Recognition Based on 4 Dimensions Local Binary Patterns.

Chao Wang,Jucheng Yang,Yarui Chen,Chao Wu,Song Dong,Xiaoyuan Zhang

Communications and Networking in China (CHINACOM)（2014）

Tianjin Univ Sci & Technol

Cited 2|Views27

Abstract

In face recognition, LBP (Local Binary Patterns) is a very popular method, which can solve the defects of the traditional local feature extraction methods with fixed scale and small extraction scale. However, the LBP operator only describes the relationship between the center pixel and its neighborhood pixels, it ignores the relationship among the operators. 3DLBP (3 Dimensions Local Binary Patterns) operator embodies this relationship to get a better local description. However, both of them neglect the center pixel value, which also reflects some properties of the image points. In this paper, we propose a novel face recognition method based on 4DLBP (4 Dimensions Local Binary Patterns), which adds the pixel value of the center point into the 3DLBP features for face recognition. We firstly partition the face image into small blocks, and then we extract the 4DLBP features of the blocked images, and combine the features to obtain the final facial features. Finally, we use the extreme learning machine (ELM) as classifier to train and classify the face images. The experimental results show the proposed method has better performances than the traditional methods.

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Key words

LBP,3DLBP,4DLBP,face recognition,ELM

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
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