基于创意序列学习的艺术风格学习与绘制系统  

Creative Sequential Data Learning Method for Artistic Stylisation and Rendering System

作　　者：谢宁 赵婷婷 杨阳 魏琴[4] Heng Tao SHEN XIE Ning;ZHAO Ting-Ting;YANG Yang;WEI Qin;Heng Tao SHEN(Center for Future Media, University of Electronic Science and Technology of China, Chengdu 611731, China;School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China;School of Computer Science and Information Engineering, Tianjin University of Science and Technology, Tianjin 300457, China;Guizhou Provincial Key Laboratory of Public Big Data （Guizhou University）, Guiyang 550025, China)

机构地区：[1]电子子科技大学未来媒体研究中心,四川成都611731 [2]电子科技大学计算机科学与工程学院,四川成都611731 [3]天津科技大学计算机科学与信息工程学院,天津300457 [4]贵州省公共大数据重点实验室贵州大学,贵州贵阳550025

出　　处：《软件学报》2018年第4期1071-1084,共14页Journal of Software

基　　金：国家自然科学基金(61602088,61572108,61632007);中央高校基本科研业务费(ZYGX2016J212,ZYGX2014Z007,ZYGX2015J055);国家重点基础研究发展计划(973)(2015CB856000)

摘　　要：在众多传统艺术绘画形式中,笔触是被现代计算机绘画工具(GIMP、Photoshop和Painter)普遍采用的形式之一.创新性地提出了服务于非真实感渲染AI辅助艺术创作系统(A4).系统能够实现自动生成特定艺术家风格的笔触效果.该系统在强化学习框架下,主要进行以下研究工作:(1)提出基于PGPE的正则化策略学习方法以提高风格学习过程的稳定性;(2)利用IRL(inverse reinforcement learning)算法实现了艺术风格行为的模型化及其数字化保护方法.实验结果表明,所提方法行之有效地实现了针对具体个性风格的照片水墨画艺术风格转化.Among various traditional art forms,brush stroke drawing is one of the widely used styles in modern computer graphic tools such as GIMP,Photoshop and Painter.In this paper,an AI-aided art authoring（A4）system of non-photorealistic rendering is developed that allows users to automatically generate brush stroke paintings in a specific artist＇s style.Within the reinforcement learning framework of brush stroke generation,the first contribution in this paper is the application of regularized policy gradient method,which is more suitable for the stroke generation task.The other contribution is to learn artists＇ drawing styles from video-captured stroke data by inverse reinforcement learning.Experiments demonstrate that the presented system can successfully learn artists＇ styles and render pictures with consistent and smooth brush strokes.

关 键 词：多媒体信息处理 序列数据分析 图像风格化 基于笔触的合成 逆向强化学习 策略探索 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]