Practical pose normalizaiton for pose-invariant face recognition

Zhongjun Wu, Shan Li, Weihong Deng
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引用次数: 1

Abstract

Identifying subjects with variations caused by poses is one of the most challenging problems in face recognition, essentially, a misalignment problem. In this paper, we propose a simple, practical but effective continuous pose normalization method to handle pose variations. First, 2D-3D correspondence is constructed based on five facial landmarks of query image. A single reference 3D mesh is projected onto query image and appearance of query face is assigned to the reference mesh. Frontal view of query face is obtained by rendering the appearance-assigned 3D mesh at frontal pose. Large scale recognition experiments conducted on MultiPIE and FERET databases show that our method achieves competitive, high recognition accuracy, with advantage of database independent and running fast, which is very suitable for practical applications.
姿态不变人脸识别的实用姿态归一化
识别由姿态引起的受试者变化是人脸识别中最具挑战性的问题之一,本质上是一个错位问题。本文提出了一种简单、实用、有效的连续姿态归一化方法来处理姿态变化。首先,基于查询图像的5个面部地标构建2D-3D对应关系;将单个参考三维网格投影到查询图像上,并将查询面外观分配给参考网格。查询人脸的正面视图是通过在正面姿态上渲染外观分配的三维网格来获得的。在MultiPIE和FERET数据库上进行的大规模识别实验表明,该方法具有具有竞争力、较高的识别精度、与数据库无关、运行速度快等优点,非常适合实际应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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