Reducing the feature vector length in local binary pattern based face recognition

@article{Lahdenoja2005ReducingTF,
  title={Reducing the feature vector length in local binary pattern based face recognition},
  author={Olli Lahdenoja and Mika Laiho and Ari Paasio},
  journal={IEEE International Conference on Image Processing 2005},
  year={2005},
  volume={2},
  pages={II-914}
}
In this paper we propose a method for reducing the length of the feature vectors in the local binary pattern (LBP) based face recognition. This is done to speed up the matching of the feature vectors in real-time face recognition and detection systems. We define a new discrimination concept of the uniform local binary patterns called symmetry. Patterns are assigned different levels of symmetry based on the number of ones or zeros they contain. These symmetry levels are rotation invariant… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 37 CITATIONS

A Shape-Preserving Non-parametric Symmetry Transform

  • 18th International Conference on Pattern Recognition (ICPR'06)
  • 2006
VIEW 7 EXCERPTS
CITES BACKGROUND
HIGHLY INFLUENCED

AMassively Parallel Face Recognition System

VIEW 7 EXCERPTS
CITES METHODS, RESULTS & BACKGROUND
HIGHLY INFLUENCED

Unsupervised LBP histogram selection for color texture classification via sparse representation

  • 2018 IEEE International Conference on Information Communication and Signal Processing (ICICSP)
  • 2018

Light field local binary patterns description for face recognition

  • 2017 IEEE International Conference on Image Processing (ICIP)
  • 2017
VIEW 3 EXCERPTS
CITES BACKGROUND

References

Publications referenced by this paper.
SHOWING 1-8 OF 8 REFERENCES

Maenpaa, “Multiresolution Gray-scale and Rotation Invariant Texture Classification with Local Binary Patterns

T. Ojala, T. M. Pietikainen
  • IEEE Transactions on Pattern Analysis and Machine Intelligence,
  • 2002
VIEW 9 EXCERPTS
HIGHLY INFLUENTIAL

Texture Classification by Subsets of Local Binary Patterns

T. Maenpaa, et.al, “Robust
  • Proceedings of the 15th International Conference on Pattern Recognition,
  • 2000
VIEW 10 EXCERPTS
HIGHLY INFLUENTIAL

Robust Texture Classi fi cation by Subsets of Local Binary Patterns ”

J. R. Beveridge, M. Texeira, B. A. Draper
  • Proceedings of the 15 th International Conference on Pattern Recognition
  • 2003

Multiresolution Grayscale and Rotation Invariant Texture Classi fi cation with Local Binary Patterns ”

M. Pietikainen, T. Maenpaa
  • IEEE Transactions on Pattern Analysis and Machine Intelligence

Similar Papers

Loading similar papers…