Three dimensional objects recognition & pattern recognition technique; related challenges: A review

被引:0
|
作者
Shilpa Rani
Kamlesh Lakhwani
Sandeep Kumar
机构
[1] Research Scholar,Assistant Professor, Department of CSE
[2] Lovely Professional University,Professor, Department of CSE
[3] Neil Gogte Institute of Technology,undefined
[4] Associate Professor,undefined
[5] JECRC University,undefined
[6] Koneru Lakshmaiah Education Foundation,undefined
来源
Multimedia Tools and Applications | 2022年 / 81卷
关键词
Local feature; Global feature; 3D object recognition; Pattern recognition;
D O I
暂无
中图分类号
学科分类号
摘要
3D object recognition and pattern recognition are active and fast-growing research areas in the field of computer vision. It is mandatory to define the pattern class, feature extraction, design classifiers, clustering, and selection of test datasets and evaluate performance for any pattern recognition system. The pattern recognition system recognizes the object, so it is required to extract the features in such a way that it will be suitable for a particular recognition method. Features can be retrieved either locally or globally. The object recognition technique is divided into two parts: the local feature extraction method and the global feature extraction method. Many researchers have done admirable work in the field of local and global feature extraction. Local feature-based techniques are more suitable for the real-world scene. The Global feature-based methods are more suitable for retrieving the 3D model & identifying the object’s shape when the object’s geometric structure is fragile.
引用
收藏
页码:17303 / 17346
页数:43
相关论文
共 50 条
  • [31] Review of Electromyographic Control Systems Based on Pattern Recognition
    Ahmad, S. A.
    Ishak, A. J.
    Ali, S. H.
    5TH KUALA LUMPUR INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING 2011 (BIOMED 2011), 2011, 35 : 556 - +
  • [32] Syntactic Pattern Recognition in Computer Vision: A Systematic Review
    Astolfi, Gilberto
    Cesar Rezende, Fabio Prestes
    De Andrade Porto, Joao Vitor
    Matsubara, Edson Takashi
    Pistori, Hemerson
    ACM COMPUTING SURVEYS, 2022, 54 (03)
  • [33] USE OF A PATTERN-RECOGNITION TECHNIQUE TO CONTROL A MULTIFUNCTIONAL PROSTHESIS
    AGHILI, F
    HAGHPANAHI, M
    MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, 1995, 33 (03) : 504 - 508
  • [34] HVDC Converter Station Protection Based on Pattern Recognition Technique
    Hekal, N. A.
    El Zoghby, H. M.
    Mohamed, S. M.
    2017 NINETEENTH INTERNATIONAL MIDDLE-EAST POWER SYSTEMS CONFERENCE (MEPCON), 2017, : 31 - 36
  • [35] Two-Dimensional Hidden Markov Models for Pattern Recognition
    Bobulski, Janusz
    Adrjanowicz, Lukasz
    ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, PT I, 2013, 7894 : 515 - 523
  • [36] Review on Reliable Pattern Recognition with Machine Learning Techniques
    Bhamare, Devyani
    Suryawanshi, Poonam
    FUZZY INFORMATION AND ENGINEERING, 2018, 10 (03) : 362 - 377
  • [37] Three decades of statistical pattern recognition paradigm for SHM of bridges
    Figueiredo, Eloi
    Brownjohn, James
    STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2022, 21 (06): : 3018 - 3054
  • [38] On the Study of moving Objects Detection and Pattern Recognition using LS-SVM
    Ge, Guangying
    Tian, Cunwei
    Wang, Minggong
    2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23, 2008, : 2486 - 2490
  • [39] Three-dimensional connectivity index for texture recognition
    Florindo, Joao B.
    Landini, Gabriel
    Bruno, Odemir M.
    PATTERN RECOGNITION LETTERS, 2016, 84 : 239 - 244
  • [40] Application of a pattern recognition method to estimate wind loads on ships and marine objects
    Valcic, M.
    Prpic-Orsic, J.
    Vucinic, D.
    MATERIALWISSENSCHAFT UND WERKSTOFFTECHNIK, 2017, 48 (05) : 387 - 399