DocumentCode :
3429707
Title :
Accurate and Robust 3D Facial Capture Using a Single RGBD Camera
Author :
Yen-Lin Chen ; Hsiang-Tao Wu ; Fuhao Shi ; Xin Tong ; Jinxiang Chai
fYear :
2013
fDate :
1-8 Dec. 2013
Firstpage :
3615
Lastpage :
3622
Abstract :
This paper presents an automatic and robust approach that accurately captures high-quality 3D facial performances using a single RGBD camera. The key of our approach is to combine the power of automatic facial feature detection and image-based 3D nonrigid registration techniques for 3D facial reconstruction. In particular, we develop a robust and accurate image-based nonrigid registration algorithm that incrementally deforms a 3D template mesh model to best match observed depth image data and important facial features detected from single RGBD images. The whole process is fully automatic and robust because it is based on single frame facial registration framework. The system is flexible because it does not require any strong 3D facial priors such as blend shape models. We demonstrate the power of our approach by capturing a wide range of 3D facial expressions using a single RGBD camera and achieve state-of-the-art accuracy by comparing against alternative methods.
Keywords :
cameras; face recognition; feature extraction; image matching; image reconstruction; image registration; 3D facial expressions; 3D facial reconstruction; 3D template mesh model; automatic approach; automatic facial feature detection technique; depth image data matching; high-quality 3D facial performance; image-based 3D nonrigid registration technique; image-based nonrigid registration algorithm accuracy; robust 3D facial capture; robust image-based nonrigid registration algorithm; single-RGBD camera; single-frame facial registration framework; Cameras; Data models; Deformable models; Face; Facial features; Solid modeling; Three-dimensional displays; 3D facial modeling; facial capture; facial feature detection; kinect; nonrigid registration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision (ICCV), 2013 IEEE International Conference on
Conference_Location :
Sydney, NSW
ISSN :
1550-5499
Type :
conf
DOI :
10.1109/ICCV.2013.449
Filename :
6751561
Link To Document :
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