{"title":"Recognition of Facial Expressions of Animation Characters Using Dominant Colors and Feature Points","authors":"Seok-Woo Jang, Gye-Young Kim, Hyun-Suk Na","doi":"10.3745/KIPSTB.2011.18B.6.375","DOIUrl":null,"url":null,"abstract":"This paper suggests a method to recognize facial expressions of animation characters by means of dominant colors and feature points. The proposed method defines a simplified mesh model adequate for the animation character and detects its face and facial components by using dominant colors. It also extracts edge-based feature points for each facial component. It then classifies the feature points into corresponding AUs(action units) through neural network, and finally recognizes character facial expressions with the suggested AU specification. Experimental results show that the suggested method can recognize facial expressions of animation characters reliably.","PeriodicalId":122700,"journal":{"name":"The Kips Transactions:partb","volume":"32 10","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Kips Transactions:partb","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3745/KIPSTB.2011.18B.6.375","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper suggests a method to recognize facial expressions of animation characters by means of dominant colors and feature points. The proposed method defines a simplified mesh model adequate for the animation character and detects its face and facial components by using dominant colors. It also extracts edge-based feature points for each facial component. It then classifies the feature points into corresponding AUs(action units) through neural network, and finally recognizes character facial expressions with the suggested AU specification. Experimental results show that the suggested method can recognize facial expressions of animation characters reliably.