Gait Object Extraction and Recognition in Dynamic and Complex Scene Using Pulse Coupled Neural Network and Feature Fusion

被引：8
|
作者：
Hou, Yimin [1 ,2 ]
Rao, Nini [1 ]
Lun, Xiangmin [2 ]
Liu, Feng [2 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Life Sci & Technol, Chengdu 610054, Peoples R China
[2] Northeast Dianli Univ, Sch Automat Engn, Chuanying 132012, Jilin, Peoples R China
来源：
JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS | 2014年 / 4卷 / 02期
关键词：
Gait Recognition; Dynamic and Complex Scene; Pulse Coupled Neural Network; Feature Fusion; IMAGE; TRANSFORM;
D O I：
10.1166/jmihi.2014.1257
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
This paper proposes a gait object extraction and recognition algorithm in dynamic and complex scene. The improved Pulse Coupled Neural Network (PCNN) is used to extract the gait objects. The initial gait image is employed to train the PCNN and the trained network is used to classify the images followed. After the gait object being extracted and normalized, the gait features, including Gait Energy Image (GEI), Procrustes mean shape, the Fan-Beam transform of GEI and the feature matrix are employed to recognize the gait object. The features above were fused by Euclidean Distance. The image sequences taken from public database and daily life were used in the experiment. The results showed that the method proposed in this paper is effective for dynamic and complex scene.
引用
收藏
页码：325 / 330
页数：6
相关论文
共 50 条
  • [21] Articulatory feature extraction for speech recognition using neural network
    Huda, Mohammad Nurul
    Hasan, Mohammad Mahedi
    Hassan, Foyzul
    Kotwal, Mohammed Rokibul Alam
    Muhammad, Ghulam
    Rahman, Chowdhury Mofizur
    International Review on Computers and Software, 2011, 6 (01) : 25 - 31
  • [22] Feature Extraction using Wavelet-PCA and Neural network for application of Object Classification & Face Recognition
    Chitaliya, N. G.
    Trivedi, A. I.
    2010 SECOND INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING AND APPLICATIONS: ICCEA 2010, PROCEEDINGS, VOL 1, 2010, : 510 - 514
  • [23] BRAIN TUMOR DETECTION USING SELECTIVE SEARCH AND PULSE-COUPLED NEURAL NETWORK FEATURE EXTRACTION
    Niepceron, Brad
    Grassia, Filippo
    Moh, Ahmed Nait Sidi
    COMPUTING AND INFORMATICS, 2022, 41 (01) : 253 - 270
  • [24] Pulse coupled neural network sensor fusion
    Johnson, JL
    Schamschula, MP
    Inguva, R
    Caulfield, HJ
    SENSOR FUSION: ARCHITECTURES, ALGORITHMS, AND APPLICATIONS II, 1998, 3376 : 219 - 226
  • [25] Feature extraction and fusion network for salient object detection
    Dai, Chao
    Pan, Chen
    He, Wei
    MULTIMEDIA TOOLS AND APPLICATIONS, 2022, 81 (23) : 33955 - 33969
  • [26] Feature extraction and fusion network for salient object detection
    Chao Dai
    Chen Pan
    Wei He
    Multimedia Tools and Applications, 2022, 81 : 33955 - 33969
  • [27] Multistage multimodal medical image fusion model using feature-adaptive pulse coupled neural network
    Singh, Sneha
    Gupta, Deep
    INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, 2021, 31 (02) : 981 - 1001
  • [28] Feature-Based Fusion of Dual Band Infrared Image Using Multiple Pulse Coupled Neural Network
    He Y.
    Wei S.
    Yang T.
    Jin W.
    Liu M.
    Zhai X.
    Journal of Beijing Institute of Technology (English Edition), 2019, 28 (01): : 129 - 136
  • [29] Feature-Based Fusion of Dual Band Infrared Image Using Multiple Pulse Coupled Neural Network
    Yuqing He
    Shuaiying Wei
    Tao Yang
    Weiqi Jin
    Mingqi Liu
    Xiangyang Zhai
    JournalofBeijingInstituteofTechnology, 2019, 28 (01) : 129 - 136
  • [30] An Evaluation of the Image Recognition Method Using Pulse Coupled Neural Network
    Yonekawa, Masato
    Kurokawa, Hiroaki
    ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2011, PT I, 2011, 6791 : 217 - 224
12345