3D facial expression modeling based on facial landmarks in single image

被引:13
|
作者
Lv, Chenlei [1 ,2 ]
Wu, Zhongke [1 ,2 ]
Wang, Xingce [1 ,2 ]
Zhou, Mingquan [1 ,2 ]
机构
[1] Beijing Normal Univ, Coll Informat Sci & Technol, Beijing, Peoples R China
[2] Beijing Normal Univ, Beijing Key Lab Digital Preservat & Virtual Real, Minist Educ, Engn Res Ctr Virtual Real & Applicat, Beijing 100875, Peoples R China
基金
北京市自然科学基金; 国家重点研发计划;
关键词
Facial expression modeling; Kendall shape space; Head poses; FACE; RECOGNITION;
D O I
10.1016/j.neucom.2019.04.050
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Facial expression modeling is important for many applications such as human emotional analysis and facial animation. Generally, facial expression modeling from single 2D facial image is difficult. Different head poses and scales of facial data in images affect the accuracy of the modeling results. We propose a new 3D facial expression modeling method which is based on facial landmarks from single image. Using the facial landmarks, expression modeling can be processed in Kendall shape space. The Kendall shape space is mathematic space, the facial expression modeling process in Kendall shape space can be regarded as a geodesic path search between different faces. The modeling result is more accurate. The 3D facial expression modeling result is convenient to obtain from 2D facial image with different head poses. In experiments, we show the 3D facial expression modeling performance by our method, which include expression editing and evaluation in public facial database: JAFFE, LFW, Helen and RAF-DB. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码:155 / 167
页数:13
相关论文
共 50 条
  • [21] Recognition of 3D emotional facial expression based on handcrafted and deep feature combination
    Hariri, Walid
    Farah, Nadir
    PATTERN RECOGNITION LETTERS, 2021, 148 (148) : 84 - 91
  • [22] Entropy-based feature selection for improved 3D facial expression recognition
    Yurtkan, Kamil
    Demirel, Hasan
    SIGNAL IMAGE AND VIDEO PROCESSING, 2014, 8 (02) : 267 - 277
  • [23] Adaptive 3D Model-Based Facial Expression Synthesis and Pose Frontalization
    Hong, Yu-Jin
    Choi, Sung Eun
    Nam, Gi Pyo
    Choi, Heeseung
    Cho, Junghyun
    Kim, Ig-Jae
    SENSORS, 2020, 20 (09)
  • [24] 3D Facial Expression Classification Based On Self-Organizing Mapping Network
    Yin, Xiaojuan
    Ju, Quan
    Li, Shuhong
    2013 SEVENTH INTERNATIONAL CONFERENCE ON INTERNET COMPUTING FOR ENGINEERING AND SCIENCE (ICICSE 2013), 2013, : 128 - 132
  • [25] 3D Facial Similarity Measurement and Its Application in Facial Organization
    Lv, Chenlei
    Wu, Zhongke
    Wang, Xingce
    Zhou, Mingquan
    ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2020, 16 (03)
  • [26] The effect of sex and age on facial shape directional asymmetry in adults: A 3D landmarks-based method study
    Harnadkova, Katarina
    Kocandrlova, Karolina
    Jaklova, Lenka Kozejova
    Dupej, Jan
    Veleminska, Jana
    PLOS ONE, 2023, 18 (08):
  • [27] Enhanced spatio-temporal 3D CNN for facial expression classification in videos
    Khanna, Deepanshu
    Jindal, Neeru
    Rana, Prashant Singh
    Singh, Harpreet
    MULTIMEDIA TOOLS AND APPLICATIONS, 2024, 83 (04) : 9911 - 9928
  • [28] 3D Mechanical Modeling of Facial Soft Tissue for Surgery Simulation
    Mazza, Edoardo
    Barbarino, Giuseppe Giovanni
    FACIAL PLASTIC SURGERY CLINICS OF NORTH AMERICA, 2011, 19 (04) : 623 - +
  • [29] A new method for automatic tracking of facial landmarks in 3D motion captured images (4D)
    Al-Anezi, T.
    Khambay, B.
    Peng, M. J.
    O'Leary, E.
    Ju, X.
    Ayoub, A.
    INTERNATIONAL JOURNAL OF ORAL AND MAXILLOFACIAL SURGERY, 2013, 42 (01) : 9 - 18
  • [30] 3-D Facial Landmarks Detection for Intelligent Video Systems
    Hoang, Van-Thanh
    Huang, De-Shuang
    Jo, Kang-Hyun
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2021, 17 (01) : 578 - 586