{"title":"A two-stage estimation method for depth estimation of facial landmarks","authors":"Xun Gong, Zehua Fu, Xinxin Li, Lin Feng","doi":"10.1109/ISBA.2015.7126355","DOIUrl":null,"url":null,"abstract":"To address the problem of 3D face modeling based on a set of landmarks on images, the traditional feature-based morphable model, using face class-specific information, makes direct use of these 2D points to infer a dense 3D face surface. However, the unknown depth of landmarks degrades accuracy considerably. A promising solution is to predict the depth of landmarks at first. Bases on this idea, a two-stage estimation method is proposed to compute the depth value of landmarks from two images. And then, the estimated 3D landmarks are applied to a deformation algorithm to make a precise 3D dense facial shape. Test results on synthesized images with known ground-truth show that the proposed two-stage estimation method can obtain landmarks' depth both effectively and efficiently, and further that the reconstructed accuracy is greatly enhanced with the estimated 3D landmarks. Reconstruction results of real-world photos are rather realistic.","PeriodicalId":398910,"journal":{"name":"IEEE International Conference on Identity, Security and Behavior Analysis (ISBA 2015)","volume":"231 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Identity, Security and Behavior Analysis (ISBA 2015)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISBA.2015.7126355","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
To address the problem of 3D face modeling based on a set of landmarks on images, the traditional feature-based morphable model, using face class-specific information, makes direct use of these 2D points to infer a dense 3D face surface. However, the unknown depth of landmarks degrades accuracy considerably. A promising solution is to predict the depth of landmarks at first. Bases on this idea, a two-stage estimation method is proposed to compute the depth value of landmarks from two images. And then, the estimated 3D landmarks are applied to a deformation algorithm to make a precise 3D dense facial shape. Test results on synthesized images with known ground-truth show that the proposed two-stage estimation method can obtain landmarks' depth both effectively and efficiently, and further that the reconstructed accuracy is greatly enhanced with the estimated 3D landmarks. Reconstruction results of real-world photos are rather realistic.