DOI QR코드

DOI QR Code

Using Spatial Pyramid Based Local Descriptor for Face Recognition

공간 계층적 구조 기반 지역 기술자 활용 얼굴인식 기술

  • Kim, Kyeong Tae (Division of Computer and Electronic Systems Engineering, Hankuk University of Foreign Studies) ;
  • Choi, Jae Young (Division of Computer and Electronic Systems Engineering, Hankuk University of Foreign Studies)
  • Received : 2017.02.26
  • Accepted : 2017.04.25
  • Published : 2017.05.31

Abstract

In this paper, we present a novel method to extract face representation based on multi-resolution spatial pyramid. In our method, a face is subdivided into increasingly finer sub-regions (local regions) and represented at multiple levels of histogram representations. To cope with misaligned problem, patch-based local descriptor extraction has been also developed in a novel way. To preserve multiple levels of detail in local characteristics and also encode holistic spatial configuration, histograms from all levels of spatial pyramid are integrated by using dimensionality reduction and feature combination, leading to our spatial-pyramid face feature representation. We incorporate our proposed face features into general face recognition pipeline and achieve state-of-the-art results on challenging face recognition problems.

Keywords

References

  1. J.T. Chien and C.C. Wu, "Discriminant Waveletfaces and Nearest Feature Classifiers for Face Recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24, No. 12, pp. 1644-1649, 2002. https://doi.org/10.1109/TPAMI.2002.1114855
  2. Y. Su, S. Shan, X. Chen, and W. Gao, "Hierarchical Ensemble of Global and Local Classifiers for Face Recognition," IEEE Transactions Image Processing, Vol. 18, No. 8, pp. 1885-1886, 2009. https://doi.org/10.1109/TIP.2009.2021737
  3. J. Sivic and A. Zisserman, "Efficient Visual Search Cast as Text Retrieval," IEEE Transactions Pattern Analysis and Machine Intelligence, Vol. 31, No. 4, pp. 591-606, 2009. https://doi.org/10.1109/TPAMI.2008.111
  4. L. Fei-Fei and P. Perona, "A Bayesian Hierarchical Model for Learning Natural Scene Categories," Proceeding of 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2, pp. 524-531, 2005.
  5. S. Lazebnik, C. Schmid, and J. Ponce, "Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories," Proceeding of 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2, pp. 2169-2178, 2006.
  6. Z.S. Li, J. Imai, and M. Kaneko, "Robust Face Recognition Using Block-based Bag of Words," Proceeding of International Conference on Pattern Recognition, pp. 1285-1288, 2010.
  7. Z.S. Li, J. Imai, and M. Kaneko, "Block-Based Bag of Words for Robust Face Recognition under Variant Conditions of Facial Expression," Illumination, and Partial Occlusion, IEICE Transactions on Fundamentals, Vol. 94, No. 2, pp. 533-541, 2011.
  8. Le An, M. Kafai, and B. Bhanu, "Face Recognition in Multi-Camera Surveillance Videos using Dynamic Bayesian Network," Proceeding of International Conferenceon Distributed Smart Cameras, pp.1-6, 2012.
  9. K. Mikolajczyk and C. Schmid, "A Performance Evaluation of Local Descriptors," IEEE Transactions Pattern Analysis and Machine Intelligence, Vol. 27, No. 10, pp. 1615-1630, 2005. https://doi.org/10.1109/TPAMI.2005.188
  10. T. Sim, S. Baker, and M. Bsat, "The CMU Pose, Illumination, and Expression Database," IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 25, No. 12, pp. 1615-1618, 2003. https://doi.org/10.1109/TPAMI.2003.1251154
  11. P.J. Phillips, H. Moon, S.A. Rizvi, and P.J. Rauss, "The FERET Evaluation Methodology for Face Recognition Algorithms," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, No. 10, pp. 1090-1104, 2000. https://doi.org/10.1109/34.879790
  12. G.B. Huang, M. Ramesh, T. Berg, and E. Learned-Miller, Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments, Technical Report 07-49, University of Massachusetts, Amherst, Vol. 1, No. 2, pp. 3, 2007.
  13. P. Viola and M. Jones, "Rapid Object Detection Using a Boosted Cascade of Simple Features," Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 1, pp. I-511-I518, 2001.
  14. J.Y. Choi, Y.M. Ro, and K.N. Plataniotis, "Color Local Texture Features for Color Face Recognition," IEEE Transactions on Image Processing, Vol. 21, No. 3, pp. 1366-1380, 2012. https://doi.org/10.1109/TIP.2011.2168413
  15. K. Mikolajczyk and C. Schmid, "Scale and Affine Invariant Interest Point Detectors," International J ournal of Computer Vision, Vol. 60, No. 1, pp. 63-86, 2004. https://doi.org/10.1023/B:VISI.0000027790.02288.f2
  16. A. Vedaldi and B. Fulkerson, "VLFeat-An Open and Portable Library of Computer Vision Algorithms," Proceedings of the 18th ACM International Conference on Multimedia, pp. 1469-1472, 2010.
  17. S. Hua1, G. Chen, H. Wei, and Q. Jiang, "Similarity Measure for Image Resizing Using SIFT feature," EURASIP Journal on Image and Video Processing, Vol. 6, pp. 1-11, 2012. https://doi.org/10.1007/s11760-010-0167-7
  18. D.G. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints," International Journal of Computer Vision, Vol. 60, No. 2, pp. 91-110, 2004. https://doi.org/10.1023/B:VISI.0000029664.99615.94
  19. P. Gehler and S. Nowozin, "On Feature Combination for Multiclass Object Classification," Proceeding of 2009 IEEE 12th International Conference on Computer Vision, pp. 221-228, 2009.
  20. M. Brown, G. Hua, and S. Winder, "Discriminative Learning of Local Image Descriptors," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 33, No. 1, pp. 43-57, 2011. https://doi.org/10.1109/TPAMI.2010.54
  21. S.J. Lee, C.M. Oh, and C.W. Lee, "Improved Face Recognition based on 2D-LDA using Weighted Covariance Scatter", Journal of Korea Multimedia Society, Vol. 17, No. 12, pp. 1446-1452, 2014. https://doi.org/10.9717/kmms.2014.17.12.1446
  22. J. Lu, K.N. Plataniotis, and A.N. Venetsanopoulos, "Face Recognition Using Kernel Direct Discriminant Analysis Algorithms," IEEE Transactions on Neural Networks, Vol. 14, No. 1, pp. 117-126, 2003. https://doi.org/10.1109/TNN.2002.806629
  23. M.A. Turk and A.P. Pentland, "Eigenfaces for Recognition," Journal of Cognitive Neuroscience, Vol. 3, No. 1, pp. 71-86, 1991. https://doi.org/10.1162/jocn.1991.3.1.71
  24. Leung, Thomas, Malik, and Jitendra, "Representing and Recognizing the Visual Appearance of Materials Using Three-dimensional Textons," International Journal of Computer Vision, Vol. 43, No. 1, pp. 29-44, 2001. https://doi.org/10.1023/A:1011126920638
  25. G. Csurka, C. Dance, L. Fan, J. Willamowski, and C. Bray, "Visual Categorization with Bags of Keypoints," Proceeding of ECCV Workshop on Statistical Learning in Computer Vision, Vol. 1, No. 1-22, pp. 1-2, 2004.
  26. T. Ahonen, A. Hadid, and M. Pietikainen, "Face Description with Local Binary Patterns: Application to Face Recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 28, No. 12, pp. 2037-2041, 2006. https://doi.org/10.1109/TPAMI.2006.244
  27. Y. Su, S. Shan, X. Chen, and W. Gao, "Hierarchical Ensemble of Global and Local Classifiers for Face Recognition," IEEE Transactions on Image Processing, Vol. 18, No. 8, pp. 1885-1896, 2009. https://doi.org/10.1109/TIP.2009.2021737
  28. S. Xie, S. Shan, X. Chen, and J. Chen, "Fusing Local Patterns of Gabor Magnitude and Phase for Face Recognition," IEEE Transactions on Image Processing, Vol. 19, No. 5, pp. 1349-1361, 2010. https://doi.org/10.1109/TIP.2010.2041397
  29. X. Tan and B. Triggs, "Enhanced Local Texture Feature Sets for Face Recognition under Difficult Lighting Conditions," IEEE Transactions on Image Processing, Vol. 19, No. 6, pp. 1635-1650, 2010. https://doi.org/10.1109/TIP.2010.2042645
  30. W. Hwang, H. Wang, H. Kim, S.C. Kee, and J. Kim, "Face Recognition System Using Multiple Face Model of Hybrid Fourier Feature under Uncontrolled Illumination Variation," IEEE Transactions on Image Processing, Vol. 20, No. 4, pp. 1152-1165, 2011. https://doi.org/10.1109/TIP.2010.2083674
  31. X. Tan and B. Triggs, "Fusing Gabor and LBP Feature Sets for Kernel-based Face Recognition," Proceeding of International Workshop on Analysis and Modeling of Faces and Gestures, pp. 235-249, 2007.
  32. C. Chan, M. Tahir, J. Kittler, and M. Pietikainen, "Multiscale Local Phase Quantisation for Robust Component-based Face Recognition using Kernel Fusion of Multiple Descriptors," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 35, No. 5, pp. 1164-1177, 2013. https://doi.org/10.1109/TPAMI.2012.199
  33. C. Ding, J.H Choi, D. Tao, and L.S. Davis, "Multi-directional Multi-Level Dual-Cross Patterns for Fobust Face Recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 38, No. 3, pp. 518-531, 2016. https://doi.org/10.1109/TPAMI.2015.2462338
  34. S. Liao and A.K. Jain, "Partial Face Recognition: An Alignment Free Approach," Proceeding of International Joint Conference on Biometrics, pp. 1-8, 2011.
  35. P.J. Phillips, P.J. Flynn, T. Scruggs, K.W. Bowyer, J. Chang, K. Hoffman, J. Marques, J. Min, and W. Worek, "Overview of the Face Recognition Grand Challenges," Proceeding of IEEE Conference on Computer Vision and Pattern Recognition, Vol. 1, pp. 947-954, 2005.
  36. S.I. Choi, "Feature Generation Method for Low-Resolution Face Recognition", Journal of Korea Multimedia Society, Vol. 18, No. 9, pp. 1039-1046, 2015. https://doi.org/10.9717/kmms.2015.18.9.1039

Cited by

  1. 얼굴인식 성능 향상을 위한 얼굴 전역 및 지역 특징 기반 앙상블 압축 심층합성곱신경망 모델 제안 vol.23, pp.8, 2017, https://doi.org/10.9717/kmms.2020.23.8.1019
  2. Face Recognition using Correlation Filters and Support Vector Machine in Machine Learning Approach vol.24, pp.4, 2021, https://doi.org/10.9717/kmms.2021.24.4.528