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3D Face Recognition and Compression

机译:3D人脸识别和压缩

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摘要

Face recognition using 3D images is an important area of research due to its ability to solve problems faced by 2D images like pose changes. In this chapter, a 3D face range recognition and compression system is proposed and the effect of using compressed 3D range images on the recognition rate is investigated. Compression is used to reduce the file size for faster transmission and is performed using the Set Partitioning in Hierarchical Trees (SPIHT) coding method, which is an improvement of the Embedded Zerotree Wavelet (EZW) coding method. Arithmetic Coding (AC) is also performed after SPIHT to further reduce the amount of bits transmitted. Comparing the uncompressed probe images and probe images compressed using SPIHT coding, simulation results show that the compressed image recognition rate ranges from being lower to being slightly higher than uncompressed probe image recognition rate, depending on bit rate. This proves that a 3D face range recognition system using compressed images is a feasible alternative to a system without using compressed images and should be investigated since the benefits like smaller file storage size, faster image transmission time and better recognition rates are important.
机译:使用3D图像进行人脸识别是研究的重要领域,因为它具有解决2D图像所面临的问题(如姿势变化)的能力。在本章中,提出了一种3D人脸范围识别和压缩系统,并研究了使用压缩的3D范围图像对识别率的影响。压缩用于减少文件大小以实现更快的传输,并且使用“分层树中的设置分区”(SPIHT)编码方法执行,这是对嵌入式零树小波(EZW)编码方法的改进。在SPIHT之后也执行算术编码(AC),以进一步减少传输的位数。比较未压缩探针图像和使用SPIHT编码压缩的探针图像,仿真结果表明,压缩图像识别率的范围从较低到略高于未压缩探针图像识别率,具体取决于比特率。这证明了使用压缩图像的3D面部范围识别系统是不使用压缩图像的系统的可行替代方案,因此应进行研究,因为诸如文件存储大小较小,图像传输时间更快和识别率更高的好处非常重要。

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