改进Phong光照模型的人脸去高光与重光照算法
Face Highlights Removal and Relighting Algorithm Based on Improved Phong Illumination Model
黄颖 1王泽荃 1李焱晖 1黄江平1
作者信息
- 1. 重庆邮电大学软件工程学院 重庆 400065
- 折叠
摘要
针对目前人脸重光照算法无法准确反映人脸反射情况的问题,提出了一种关于改进的Phong光照模型的人脸图像去高光算法与重光照算法.该算法主要分为三部分:1)依据该光照模型,可渲染得到合成数据集用以训练神经网络去除高光.2)利用半监督学习将去高光能力转移到真实人脸中.3)将去高光后人脸图像进一步分解为光照相关和无关分量.替换光照相关部分并重组图像,实现人脸重光照.实验结果表明,改进后的算法可提升重光照精确度与视觉效果.
Abstract
Aiming at the problem that the current face relighting algorithm can not accurately reflect the face reflection,a face image specular removal algorithm and a relighting algorithm based on the improved Phong illumination model are proposed.The algo-rithm includes three parts.1)According to the illumination model,rendered synthetic data to train the neural network to remove highlights.2)The semi-supervised learning is used to transfer the ability of specular removal to real faces.3)After specular remov-al,face image is decomposed into components related to illumination and component unrelated to illumination.The component relat-ed is replaced to illumination ande the image is recombined to achieve face illumination.Experimental results show that the im-proved algorithm can improve the relighting accuracy and visual effect.
关键词
基于图像的重光照/深度学习/光照模型/高光去除/逆渲染Key words
image-based relighting/deep learning/illumination model/specular removal/inverse rendering引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据