摘 　要 　提出了一种基于样本学习的人脸肖像画自动生成算法.文章采用非均匀的马尔科夫随机场模型来描述肖

像画与人脸图像之间的统计关系 ,并使用基于训练样本的非参数化的概率表示 ,在贝叶斯优化的框架下设计了迭

代采样算法 ,可以自动的从人脸图像生成特定风格的肖像画.在该方法中 ,使用非均匀的统计模型是保持肖像中人

脸结构准确性的关键.文中所提供的例子表明了该文方法的有效性-Abstract　In this paper , we present a new approach for automatically generating a life2like port rait

f rom a f rontal face image. We learn the port raiture f rom a set of real artwork examples. Different f rom

previous texture synthesis and image synthesis works that assumed modeling is homogeneous , Inhomo2

geneous Markov Random Field Model is employed as the statistical model , and a non2 paramet ric sam2

pling scheme is used to capture the complex statistical characteristics of face image and corresponding

artist drawing in this paper . In our st rategy , only those pixels corresponding to a port rait point are

sampled. Such a st rategy is crucial for maintaining facial st ructure and guaranteeing coherence of por2

t rait lines. Experimental result s demonst rate the effectiveness and life 2likeness of our approach.