TY - JOUR
T1 - A Topology Standardized 3D Facial Dataset with Emotion and Action Unit Diversity for East Asians
AU - Zhao, Yaopu
AU - Gong, Guanghong
AU - Li, Yan
AU - Li, Ni
AU - Liu, Yang
N1 - Publisher Copyright:
© The Author(s) 2026.
PY - 2026/12
Y1 - 2026/12
N2 - We present a high-resolution 3D facial dataset focused on East Asian participants, designed to provide consistent topology and expression diversity. The dataset includes 98 individuals (18–30 years) and captures neutral faces, six basic emotions, and nine Facial Action Coding System (FACS)-based Action Units (AUs). Each 3D mesh is acquired under a standardized protocol. Synchronized multi-view RGB images are available only for a subset of participants who provided additional consent. To ensure structural consistency across subjects and expressions, we developed a processing pipeline combining FLAME-based expression fitting with Edge-Constrained Non-rigid Iterative Closest Point (Edge-NICP). The resulting meshes share unified topology and vertex correspondence, enabling direct point-to-point comparisons across conditions. Rich annotations, including facial landmarks, verified AU labels, and vertex-level deformation fields, accompany the dataset. Together, these resources may facilitate research in computer graphics, human–computer interaction, and cross-modal studies that benefit from expression-rich, topology-standardized 3D face data.
AB - We present a high-resolution 3D facial dataset focused on East Asian participants, designed to provide consistent topology and expression diversity. The dataset includes 98 individuals (18–30 years) and captures neutral faces, six basic emotions, and nine Facial Action Coding System (FACS)-based Action Units (AUs). Each 3D mesh is acquired under a standardized protocol. Synchronized multi-view RGB images are available only for a subset of participants who provided additional consent. To ensure structural consistency across subjects and expressions, we developed a processing pipeline combining FLAME-based expression fitting with Edge-Constrained Non-rigid Iterative Closest Point (Edge-NICP). The resulting meshes share unified topology and vertex correspondence, enabling direct point-to-point comparisons across conditions. Rich annotations, including facial landmarks, verified AU labels, and vertex-level deformation fields, accompany the dataset. Together, these resources may facilitate research in computer graphics, human–computer interaction, and cross-modal studies that benefit from expression-rich, topology-standardized 3D face data.
UR - https://www.scopus.com/pages/publications/105039285109
U2 - 10.1038/s41597-026-07098-2
DO - 10.1038/s41597-026-07098-2
M3 - 文章
C2 - 41876566
AN - SCOPUS:105039285109
SN - 2052-4463
VL - 13
JO - Scientific Data
JF - Scientific Data
IS - 1
M1 - 735
ER -