Parametric face coding for invariant model representation

被引:4
|
作者
Sun, L [1 ]
Qamhiyah, AZ [1 ]
机构
[1] Iowa State Univ, Dept Engn Mech, Ames, IA 50011 USA
关键词
CAD; wavelet transforms; transformation-invariant object representation; ZERO-CROSSINGS; RECOGNITION; OBJECTS; SPACE; LINES;
D O I
10.1016/S0010-4485(02)00072-6
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
This paper addresses the development of a transformation-invariant coding system for CAD models and form features by multi-scale wavelet representations in order to automate algorithmic search and retrieval shape patterns in CAD models. The coding system is implemented in terms of the topology entity-face. A face consists of the internal surface patches and the external contours. Both the surface patch and contour information are included in the code. Discrete wavelet transforms are unstable under the translation, rotation, and dilation of an input signal. In order to overcome this limitation, one of the most intrinsic shape characteristics-curvature, which is invariant to transformation and parameterization, is used to represent the surface patches. The face contour is approximated by the radial distance function and represented by the wavelet zero-crossings. These two transformation-invariant shape descriptors are then decomposed into fine-to-coarse approximations and details by discrete wavelet transforms. A few of these wavelet detail coefficients are then selected and normalized as codes. (C) 2002 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:519 / 532
页数:14
相关论文
共 50 条
  • [41] 3D Face Representation Using Scale and Transform Invariant Features
    Akaguenduez, Erdem
    Ulusoy, Ilkay
    2008 IEEE 16TH SIGNAL PROCESSING, COMMUNICATION AND APPLICATIONS CONFERENCE, VOLS 1 AND 2, 2008, : 14 - 17
  • [42] Single-Image Expression Invariant Face Recognition Based on Sparse Representation
    Su, Ya
    Wang, Mengyao
    NEURAL INFORMATION PROCESSING, ICONIP 2015, PT IV, 2015, 9492 : 216 - 223
  • [43] Viewpoint-invariant face recognition based on view-based representation
    Chung, Jinyun
    Lee, Juho
    Park, Hyun Jin
    Yang, Hyun Seung
    COMPUTATIONAL INTELLIGENCE, PT 2, PROCEEDINGS, 2006, 4114 : 872 - 878
  • [44] INVARIANT MOTION REPRESENTATION LEARNING FOR 3D TALKING FACE SYNTHESIS
    Liu, Jiyuan
    Wei, Wenping
    Li, Zhendong
    Li, Guanfeng
    Liu, Hao
    2024 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, ICASSP 2024, 2024, : 4700 - 4704
  • [45] A robust invariant bipolar representation for R 3 surfaces: applied to the face description
    Ghorbel, Faouzi
    Jribi, Majdi
    ANNALS OF TELECOMMUNICATIONS, 2013, 68 (3-4) : 219 - 230
  • [46] A 3D Face Model for Pose and Illumination Invariant Face Recognition
    Paysan, Pascal
    Knothe, Reinhard
    Amberg, Brian
    Romdhani, Sami
    Vetter, Thomas
    AVSS: 2009 6TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED VIDEO AND SIGNAL BASED SURVEILLANCE, 2009, : 296 - 301
  • [47] Face Recognition based on Illumination Invariant Techniques Model
    Maw, Hla Myat
    Thu, Soe Myat
    Mon, Myat Thida
    2019 INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION TECHNOLOGIES (ICAIT), 2019, : 120 - 125
  • [48] A Model Based Approach for Expressions Invariant Face Recognition
    Riaz, Zahid
    Mayer, Christoph
    Wimmer, Matthias
    Beetz, Michael
    Radig, Bernd
    ADVANCES IN BIOMETRICS, 2009, 5558 : 289 - 298
  • [49] A hierarchical compositional model for face representation and sketching
    Xu, Zijian
    Chen, Hong
    Zhu, Song-Chun
    Luo, Jiebo
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2008, 30 (06) : 955 - 969
  • [50] General Regression and Representation Model for Face Recognition
    Qian, Jianjun
    Yang, Jian
    2013 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW), 2013, : 166 - 172