Dynamic biometric identification from multiple views using the GLBP-TOP method.

@article{Wang2014DynamicBI,
  title={Dynamic biometric identification from multiple views using the GLBP-TOP method.},
  author={Yu Wang and Xuanjing Shen and Haipeng Chen and Yujie Zhai},
  journal={Bio-medical materials and engineering},
  year={2014},
  volume={24 6},
  pages={
          2715-24
        }
}
To realize effective and rapid dynamic biometric identification with low computational complexity, a video-based facial texture program that extracts local binary patterns from three orthogonal planes in the frequency domain of the Gabor transform (GLBP-TOP) was proposed. Firstly, each normalized face was transformed by Gabor wavelet to get the enhanced Gabor magnitude map, and then the LBP-TOP operator was applied to the maps to extract video texture. Finally, weighted Chi square statistics… 
2 Citations

Figures and Tables from this paper

Video Face Recognition Based on Modified Fisher Criteria and Multi-instance Learning
TLDR
A video face recognition algorithm based on multi-instance learning that can achieve a higher recognition accuracy, and at the same time, the method is robust to illumination variation and expression variation.
ST-VLAD: Video Face Recognition Based on Aggregated Local Spatial-Temporal Descriptors
TLDR
A novel video face recognition algorithm is proposed based on an aggregated local spatial-temporal descriptor (ST-VLAD), followed by a novel Fisher Criterion-based weight-learning method, which portrays the local information of the video more accurately, therefore largely improving the representation ability of description vectors.

References

SHOWING 1-10 OF 20 REFERENCES
Face Recognition with Local Binary Patterns
TLDR
The principles of the LBP method and implementation to perform face recognition are presented and high recognition rates are obtained, especially compared to other face recognition methods.
Face Recognition with Local Binary Patterns
TLDR
A novel approach to face recognition which considers both shape and texture information to represent face images and the simplicity of the proposed method allows for very fast feature extraction.
Weight-Based Facial Expression Recognition from Near-Infrared Video Sequences
TLDR
A novel weight-based approach to recognize facial expressions from the near-infrared (NIR) video sequences by setting different weights for each of the three planes (appearance, horizontal motion and vertical motion) inside the block volume.
Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition
TLDR
A novel Gabor-Fisher (1936) classifier (GFC) for face recognition is introduced, which applies the enhanced Fisher linear discriminant model (EFM) to an augmented Gabor feature vector derived from the Gabor wavelet representation of face images.
Local Binary Patterns and Its Application to Facial Image Analysis: A Survey
TLDR
As a typical application of the LBP approach, LBP-based facial image analysis is extensively reviewed, while its successful extensions, which deal with various tasks of facial imageAnalysis, are also highlighted.
Face Description with Local Binary Patterns: Application to Face Recognition
TLDR
This paper presents a novel and efficient facial image representation based on local binary pattern (LBP) texture features that is assessed in the face recognition problem under different challenges.
Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions
TLDR
A novel approach for recognizing DTs is proposed and its simplifications and extensions to facial image analysis are also considered and both the VLBP and LBP-TOP clearly outperformed the earlier approaches.
Expression Recognition in Videos Using a Weighted Component-Based Feature Descriptor
TLDR
Experimental results on the Extended Cohn-Kanade database show that the approach combining component-based spatiotemporal features descriptor and weight learning strategy achieves better recognition performance than the state of the art methods.
Multiscale Local Phase Quantization for Robust Component-Based Face Recognition Using Kernel Fusion of Multiple Descriptors
TLDR
A novel blur-robust face image descriptor based on Local Phase Quantization is proposed and extended to a multiscale framework (MLPQ) to increase its effectiveness and provide a new insight into the merits of various face representation and fusion methods, as well as their role in dealing with variable lighting and blur degradation.
Combining appearance and motion for face and gender recognition from videos
...
...