从侧面视图图像中确定面部角度的鲁棒自动视觉方法

S. Singaravelan, D. Murugan
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引用次数: 1

摘要

人脸图像的分析由于其众多的应用而变得越来越重要。在这方面,人脸参数的提取是至关重要的,在这方面已经进行了各种研究。因此,在我们所提出的工作中,首次引入了一种鲁棒的基于radon变换的人脸角度自动确定方法。Radon变换是一种沿特定方向的线性积分,而角度在这种变换中起着重要的作用。通过构建线性判别分析(LDA)来考虑全局特征,通过局部保持投影(LPP)来考虑局部特征。该算法不仅精度高,而且在噪声、尺度和旋转图像环境下具有良好的性能和鲁棒性。在这项工作中,已经进行了几个实验来分析我们提出的Radon组合全局和局部保持特征(RCGLPF)算法以及其他现有的传统算法的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust automatic visual method for determining facial angles from profile view images
A analysis of human facial images has become increasingly important due to its numerous applications. In this regards, extracting facial parameter is vital and various studies have been done in this field. Hence in our proposed work, first time up to our knowledge, a robust automatic method is introduced for determining facial angles from profile view images using radon transform. Radon transform is a kind of linear integration along a specific direction and angles play an important role to do this transform. The global features were rather considered by constructing a linear discriminant analysis (LDA) and also local features were rather considered by locality preserving projection (LPP). Our proposed combined algorithm has not only good precision, but also efficient performance and robust with noisy, scale and rotated image environments. In this work, several experiments have been conducted to analyze the robustness of our proposed Radon Combined Global and Local Preserving Features (RCGLPF) algorithm along with other existing conventional algorithms.
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