局部二值模式方法及其在人脸分析中的应用

A. Hadid
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引用次数: 61

摘要

局部二值模式(LBP)算子是一种灰度不变的纹理测度,由局部邻域纹理的一般定义衍生而来。由于其判别能力和计算简单,LBP纹理算子已成为各种应用的流行方法,包括视觉检测,图像检索,遥感,生物医学图像分析,运动分析,环境建模和户外场景分析。近年来的研究表明,局部二值模式纹理方法在静态图像和视频序列中的人脸表示和分析方面也取得了显著的效果。本文描述了将在图像处理理论、工具和应用国际研讨会(IPTA'08)上讲授的教程,并概述了将LBP方法应用于各种人脸分析相关任务,包括眼睛检测、人脸识别、人脸检测、面部表情识别、视觉语音识别和性别分类。
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The Local Binary Pattern Approach and its Applications to Face Analysis
The local binary pattern (LBP) operator is defined as a gray-scale invariant texture measure, derived from a general definition of texture in a local neighborhood. Due to its discriminative power and computational simplicity, the LBP texture operator has become a popular approach in various applications, including visual inspection, image retrieval, remote sensing, biomedical image analysis, motion analysis, environment modelling, and outdoor scene analysis. Recent developments showed that the local binary pattern texture method also provides outstanding results in representing and analyzing faces in both still images and video sequences. This paper describes the tutorial that will be lectured at The International Workshops on Image Processing Theory, Tools and Applications (IPTA'08) and presents an overview of applying LBP approach to various face analysis related tasks, including eye detection, face recognition, face detection, facial expression recognition, visual-speech recognition and gender classification.
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