Tanasai Sucontphunt, Xiaoru Yuan, Qing Li, Z. Deng
{"title":"A Novel Visualization System for Expressive Facial Motion Data Exploration","authors":"Tanasai Sucontphunt, Xiaoru Yuan, Qing Li, Z. Deng","doi":"10.1109/PACIFICVIS.2008.4475465","DOIUrl":null,"url":null,"abstract":"Facial emotions and expressive facial motions have become an intrinsic part of many graphics systems and human computer interaction applications. The dynamics and high dimensionality of facial motion data make its exploration and processing challenging. In this paper, we propose a novel visualization system for expressive facial motion data exploration. Based on Principal Component Analysis (PCA) dimensionality reduction on anatomical facial sub regions, high dimensional facial motion data is mapped to 3D spaces. We further rendered it as colored 3D trajectories and color represents different emotion. We design an intuitive interface to allow users effectively explore and analyze high dimensional facial motion spaces. The applications of our visualization system on novel facial motion synthesis and emotion recognition are demonstrated.","PeriodicalId":364669,"journal":{"name":"2008 IEEE Pacific Visualization Symposium","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE Pacific Visualization Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PACIFICVIS.2008.4475465","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Facial emotions and expressive facial motions have become an intrinsic part of many graphics systems and human computer interaction applications. The dynamics and high dimensionality of facial motion data make its exploration and processing challenging. In this paper, we propose a novel visualization system for expressive facial motion data exploration. Based on Principal Component Analysis (PCA) dimensionality reduction on anatomical facial sub regions, high dimensional facial motion data is mapped to 3D spaces. We further rendered it as colored 3D trajectories and color represents different emotion. We design an intuitive interface to allow users effectively explore and analyze high dimensional facial motion spaces. The applications of our visualization system on novel facial motion synthesis and emotion recognition are demonstrated.