Automatic 3D Facial Landmark-Based Deformation Transfer on Facial Variants for Blendshape Generation

被引:2
|
作者
Ingale, Anupama K. K. [1 ]
Leema, A. Anny [1 ,4 ]
Kim, HyungSeok [2 ]
Udayan, J. Divya [3 ]
机构
[1] Vellore Inst Technol, Sch Informat Sci & Engn, Vellore, Tamil Nadu, India
[2] Konkuk Univ, Dept Comp Engn, Seoul, South Korea
[3] Amrita Vishwa Vidyapeetham, Dept Comp Sci & Engn, Amritapuri Campus, Amritapuri, Kerala, India
[4] Vellore Inst Technol, Sch Comp Sci & Engn, Vellore, India
关键词
Blendshapes; Expression transfer; Facial landmarks; Deformation transfer; Facial animation;
D O I
10.1007/s13369-022-07403-2
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Blendshape models are used in various computer vision applications, such as expression transfer, 3D reconstruction, expression analysis and so on. Blendshape models have received lot of attention in last decades, and extensive research is carried out in the 3D face modeling. Computer-based animations use blendshape models for the transfer of target facial expression to animated character. The major challenge in such animation is developing blendshape models that can represent various facial expressions. To create such large data set of expression, one requires a dedicated expert team and it is a time-consuming process. In this paper, we propose a framework for automatic facial landmark detection and blendshape generation through expression transfer. The proposed work is in two main folds: Initially, facial landmarks are extracted based on geometric information of the given facial mesh. Further, the extracted landmark points and the estimated correspondence between source and target facial models are used to perform deformation transfer. Experiment results show that our method is able to transfer expression by using automatic landmarks and also the smoothness of deformation around facial landmark areas proves that our proposed landmark-based deformation method is as good as the state-of-the-art methods. Our proposed method for automatic facial landmark detection based on geometric information of 3D face model has the ability to detect reliable correspondences, and it is faster and simpler compared with the state-of-the-art automatic deformation transfer method on the facial models.
引用
收藏
页码:10109 / 10123
页数:15
相关论文
共 50 条
  • [31] Coarse-to-fine 3D facial landmark localization based on keypoints
    Cheng X.
    Da F.
    Deng X.
    Da, Feipeng (dafp@seu.edu.cn), 2018, Science Press (39): : 256 - 264
  • [32] New Method for Locating the 3D Facial Landmark Points
    Zhang, Yongze
    Da, Feipeng
    Li, Xiaoli
    Gai, Shaoyan
    PROCEEDINGS OF THE 2009 CHINESE CONFERENCE ON PATTERN RECOGNITION AND THE FIRST CJK JOINT WORKSHOP ON PATTERN RECOGNITION, VOLS 1 AND 2, 2009, : 211 - 215
  • [33] A Novel Genetic Algorithm for 3D Facial Landmark Localization
    Yu, Tsz-Ho
    Moon, Yiu-Sang
    2008 IEEE SECOND INTERNATIONAL CONFERENCE ON BIOMETRICS: THEORY, APPLICATIONS AND SYSTEMS (BTAS), 2008, : 369 - 374
  • [34] LANDMARK IDENTIFICATION IN 3D IMAGE FOR FACIAL EXPRESSION RECOGNITION
    Sindhuja, C.
    Mala, K.
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMPUTING AND COMMUNICATIONS TECHNOLOGIES (ICCCT 15), 2015, : 338 - 343
  • [35] Deep 3D Facial Landmark Localization on position maps
    Zhang, Jingchen
    Gao, Kangkang
    Fu, Keren
    Cheng, Peng
    NEUROCOMPUTING, 2020, 406 : 89 - 98
  • [36] Deep 3D Facial Landmark Detection on Position Maps
    Gao, Kangkang
    Yang, Shanming
    Fu, Keren
    Cheng, Peng
    INTELLIGENCE SCIENCE AND BIG DATA ENGINEERING: VISUAL DATA ENGINEERING, PT I, 2019, 11935 : 299 - 311
  • [37] 3D Facial Landmark Localisation by Matching Simple Descriptors
    Romero-Huertas, Marcelo
    Pears, Nick
    2008 IEEE SECOND INTERNATIONAL CONFERENCE ON BIOMETRICS: THEORY, APPLICATIONS AND SYSTEMS (BTAS), 2008, : 346 - 351
  • [38] Automatic Generation of 3D Facial Image Using Artificial Neural Network
    Yamamoto, Takuma
    Hattori, Koosuke
    Taguchi, Ryo
    Hoguro, Masahiro
    Umezaki, Taizo
    ELECTRONICS AND COMMUNICATIONS IN JAPAN, 2014, 97 (03) : 52 - 59
  • [39] Numerical Approach to Facial Palsy Using a Novel Registration Method with 3D Facial Landmark
    Kim, Junsik
    Jeong, Hyungwha
    Cho, Jeongmok
    Pak, Changsik
    Oh, Tae Suk
    Hong, Joon Pio
    Kwon, Soonchul
    Yoo, Jisang
    SENSORS, 2022, 22 (17)
  • [40] A landmark-based data-driven approach on 2.5D facial attractiveness computation
    Liu, Shu
    Fan, Yang-Yu
    Guo, Zhe
    Samal, Ashok
    Ali, Afan
    NEUROCOMPUTING, 2017, 238 : 168 - 178