Tian, LihuiXiao, ShuangjiuEitan Grinspun and Bernd Bickel and Yoshinori Dobashi2016-10-112016-10-1120161467-8659https://doi.org/10.1111/cgf.13036https://diglib.eg.org:443/handle/10.1111/cgf13036We propose a personality trait exaggeration system emphasizing the impression of human face in images, based on multi-level features learning and exaggeration. These features are called Personality Trait Model(PTM). Abstract level of PTM is social psychology trait of face perception such as amiable, mean, cute and so on. Concrete level of PTM is shape feature and texture feature. A training phase is presented to learn multi-level features of faces from different images. Statistical survey is taken to label sample images with people's first impressions. From images with the same labels, we capture not only shape features but also texture features to enhance exaggeration effect. Texture feature is expressed by matrix to reflect depth of facial organs, wrinkles and so on. In application phase, original images will be exaggerated using PTM iteratively. And exaggeration rate for each iteration is constrained to keep likeness with the original face. Experimental results demonstrate that our system can emphasize chosen social psychology traits effectively.I.3.3 [Computer Graphics]Picture/Image Generation10.1111/cgf.13036391-399