Automatic reconstruction of dense 3D face point cloud with a single depth image

Shu Zhang, Hui Yu, Junyu Dong, Ting Wang, Zhaojie Ju, Honghai Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Human face analysis is the basis for many other computer vision tasks, such as camera surveillance, entrance authorization and age estimation. With 3D face models, the vision task based on facial analysis can usually achieve a higher accuracy than the 2D cases since it provides more information with the additional dimension. However, most existing 3D face reconstruction methods suffer from complicated processing and high computation. This paper presents a novel method that simplifies the 3D face reconstruction process with only one shot of Kinect data. The output of the system is a high density of 3D face point cloud with smoother surface. This provides rich details of the human face for other computer vision tasks. Experiments with real world data show promising results using the proposed method.
Original languageEnglish
Title of host publication2015 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
PublisherIEEE
Pages1439-1444
DOIs
Publication statusPublished - Oct 2015
Event2015 IEEE International Conference on Systems, Man, and Cybernetics - Hong Kong, China
Duration: 9 Oct 201512 Nov 2015

Conference

Conference2015 IEEE International Conference on Systems, Man, and Cybernetics
Country/TerritoryChina
CityHong Kong
Period9/10/1512/11/15

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