A comprehensive overview of feature representation for biometric recognition

被引：0
作者：
Imad Rida
Noor Al-Maadeed
Somaya Al-Maadeed
Sambit Bakshi
机构：
[1] Qatar University,Department of Computer Science and Engineering
[2] National Institute of Technology Rourkela,Department of Computer Science and Engineering
来源：
Multimedia Tools and Applications | 2020年 / 79卷
关键词：
Biometrics; Feature representation; Dimensionality reduction; Feature selection; Decomposition learning;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The performance of any biometric recognition system heavily dependents on finding a good and suitable feature representation space where observations from different classes are well separated. Unfortunately, finding this proper representation is a challenging problem which has taken a huge interest in machine learning and computer vision communities. In the this paper we present a comprehensive overview of the different existing feature representation techniques. This is carried out by introducing simple and clear taxonomies as well as effective explanation of the prominent techniques. This is intended to guide the neophyte and provide researchers with state-of-the-art approaches in order to help advance the research topic in biometrics.
引用
收藏
页码：4867 / 4890
页数：23
相关论文
共 213 条
  • [41] Amitai M(1999)Liii. on lines and planes of closest fit to systems of points in space. The London Adv Large Margin Classifiers 10 61-3248
  • [42] Konen E(2016)Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods IEEE Signal Process Lett 23 154-30
  • [43] Goldberger J(2016)Human body part selection by group lasso of motion for model-free gait recognition SIViP 10 463-2326
  • [44] Greenspan H(2019)Gait recognition based on modified phase-only correlation IET Biometrics 8 14-292
  • [45] Dijkstra EW(2018)Robust gait recognition: a comprehensive survey IEEE Access 6 3241-798
  • [46] Elad M(2019)Palmprint identification using an ensemble of sparse representations Pattern Recognition Letters 126 21-2323
  • [47] Aharon M(2000)Palmprint recognition with an efficient data driven ensemble classifier Science 290 2323-398
  • [48] Elad M(1904)Nonlinear dimensionality reduction by locally linear embedding Amer J Psychol 15 201-288
  • [49] Figueiredo MA(2010)General intelligence, objectively determined and measured IEEE Trans Pattern Anal Mach Intell 32 788-108
  • [50] Ma Y(2000)Sparse multiple kernel learning for signal processing applications Science 290 2319-622
12345678910