3D face reconstruction and recognition using the overfeat network

Yaser Saleh, E. Edirisinghe
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引用次数: 3

Abstract

Although face recognition is considered a popular area of research and study, it still has few unresolved challenges, and with the appearance of devices such as the Microsoft Kinect, new possibilities for researchers were uncovered. With the goal of enhancing face recognition techniques, this paper presents a novel way to reconstruct face images in different angles, through the use of the data of one front image captured by the Kinect, using faster techniques than ever before, also, this paper utilizes a deep learning network called Overfeat, where it functioned as a feature extractor that was used on normal images and on the new 3D created images, which introduced a new application for the network. To check the capabilities of the new created images, they were used as a testing set in three main experiments. Finally, results of the experiments are presented to prove the ability of the created images to function as new data sets for face recognition; also, proving the capability of the Overfeat network, working with computer generated face images.
基于overfeat网络的三维人脸重建与识别
尽管人脸识别被认为是一个热门的研究领域,但它仍然有一些未解决的挑战,随着微软Kinect等设备的出现,研究人员发现了新的可能性。为了增强人脸识别技术,本文提出了一种新的方法来重建不同角度的人脸图像,通过使用Kinect捕获的一个正面图像的数据,使用比以往更快的技术,此外,本文利用了一个名为Overfeat的深度学习网络,它作为一个特征提取器,用于正常图像和新的3D创建的图像,这为网络引入了一个新的应用。为了检查新创建的图像的功能,它们被用作三个主要实验的测试集。最后,给出了实验结果,证明了所创建的图像可以作为人脸识别的新数据集;同时,也证明了Overfeat网络处理计算机生成的人脸图像的能力。
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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