Representing 3D face from point cloud to face-aligned spherical depth map

CASIA OpenIR > 智能感知与计算研究中心

	Representing 3D face from point cloud to face-aligned spherical depth map
	Peijiang Liu; Yunhong Wang; Zhaoxiang Zhang
发表期刊	International Journal of Pattern Recognition and Artificial Intelligence
	2012-06-18
卷号	26 期号:1 页码:1-17
摘要	We propose a novel representation of 3D face shape which is a key step for feature extraction and face recognition. The input of the proposed methods is unstructured point cloud, which determines the wide applicability of the proposed representation. Our contributions mainly include two parts: Spherical Depth Map (SDM) and face alignment based on SDM. SDM, which can be adopted to many applications, is a special kind of range image utilizing the prior anatomical knowledge of human face. Useful characteristics of SDM facilitate face alignment with higher efficiency and accuracy. Experiments conducted on three popular 3D face databases verify the high efficacy and superiority of the proposed method. The accuracy of face alignment is up to 100% with our strategy. The face verification rates based on the standard protocols are all higher than the baseline performance of FRGC2.0.
关键词	Shape Representation Spherical Depth Map Face Alignment Pose Normalization Face Recognition
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/13224
专题	智能感知与计算研究中心
通讯作者	Zhaoxiang Zhang
推荐引用方式 GB/T 7714	Peijiang Liu,Yunhong Wang,Zhaoxiang Zhang. Representing 3D face from point cloud to face-aligned spherical depth map[J]. International Journal of Pattern Recognition and Artificial Intelligence,2012,26(1):1-17.
APA	Peijiang Liu,Yunhong Wang,&Zhaoxiang Zhang.(2012).Representing 3D face from point cloud to face-aligned spherical depth map.International Journal of Pattern Recognition and Artificial Intelligence,26(1),1-17.
MLA	Peijiang Liu,et al."Representing 3D face from point cloud to face-aligned spherical depth map".International Journal of Pattern Recognition and Artificial Intelligence 26.1(2012):1-17.