LBP特征驱动的高效人脸识别技术及应用

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"Face Description with Local Binary Patterns (LBP) 是一篇关于人脸识别的重要论文，由Timo Ahonen、Abdenour Hadid和Matti Pietikäinen三位作者提出，他们是IEEE的成员。论文的核心内容聚焦于一种新颖且高效的面部图像表示方法，利用局部二值模式（LBP）纹理特征。LBP是一种简单而有效的特征提取技术，它通过比较像素及其周围邻居的灰度值，生成一个二进制代码，从而捕捉图像的局部纹理信息。在论文中，作者首先将人脸图像划分为多个区域，然后分别提取每个区域的LBP特征分布，并将这些特征向量组合成一个增强的特征向量，作为人脸描述符。这种做法有助于保留面部细节，使得即使在面对人脸偏斜或光照变化等挑战时，也能保持较好的识别性能。作者评估了这种方法在人脸识别任务中的表现，对比了其与其他传统方法如主成分分析(PCA)的优劣。此外，文章还讨论了LBP特征在人脸识别中的应用广泛性，以及可能的扩展方向，例如针对面部错位(facemisalignment)问题的处理和在其他领域的潜在应用，如表情识别。这篇论文为基于LBP特征的人脸识别提供了有价值的技术基础，对于计算机视觉研究领域，尤其是在自动面部分析方面具有重要意义。"

1 1 0

1 0 0

Binary: 11001011

Decimal: 203

Threshold

85 99 21

54 54 86

12 1357

Fig. 1. The basic LBP operator.

extensions.

II. LBP BASED FACE DESCRIPTION

The LBP operator [11] is one of the best performing texture descriptors and it has been widely

used in various applications. It has proven to be highly discriminative and its key advantages,

namely its invariance to monotonic gray level changes and computational efﬁciency, make it

suitable for demanding image analysis tasks. For a bibliography of LBP-related research, see

http://www.ee.oulu.ﬁ/research/imag/texture/.

The idea of using LBP for face description is motivated by the fact that faces can be seen as

a composition of micro-patterns which are well described by such operator.

A. Local binary patterns

The LBP operator was originally designed for texture description. The operator assigns a label

to every pixel of an image by thresholding the 3x3-neighborhood of each pixel with the center

pixel value and considering the result as a binary number. Then the histogram of the labels can

be used as a texture descriptor. See Figure 1 for an illustration of the basic LBP operator.

To be able to deal with textures at different scales, the LBP operator was later extended to

use neighborhoods of different sizes [12]. Deﬁning the local neighborhood as a set of sampling

points evenly spaced on a circle centered at the pixel to be labeled allows any radius and number

of sampling points. Bilinear interpolation is used when a sampling point does not fall in the

center of a pixel. In the following, the notation

(

P ; R

)

will be used for pixel neighborhoods

which means

sampling points on a circle of radius of

. See Figure 2 for an example of

circular neighborhoods.

Another extension to the original operator is the deﬁnition of so called uniform patterns

[12]. A local binary pattern is called uniform if the binary pattern contains at most two bitwise

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LBP特征驱动的高效人脸识别技术及应用

Local Binary Patterns

Local Binary Pattern （LBP）纹理，基于multiresolution texture classification with local binary patterns

找一下PCA可以用于将人脸图像的表情以主要特征值的形式提取出来，从而生成新的表情。的资料

``` recognizer2 = cv2.face.LBPHFaceRecognizer_create() ```

cv2.face.LBPHFaceRecognizer_create()

人脸识别算法LBPH

TBMR局部特征提取算法

import cv2.face

What is the correct description of a binary tree?

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