Biometric Indexing

Slides (pdf)Video

Abstract

Biometric identification systems typically require one-to-many comparisons by evaluating the biometric similarity between an input query and the database records. With increasing data volume and access demand, it is necessary to develop effective and efficient methods that can help to narrow the search range and reduce the matching complexity for computationally intensive tasks such as identity de-duplication and identification based on secured templates. Biometric indexing is designed to address the problem by assigning an index vector to every identity in the database, with the aim of fast retrieving a small number of candidate identities for matching. This talk will discuss problems and recent developments of biometric indexing from three aspects, namely, accuracy, efficiency and privacy. In particular, examples of hash-based indexing methods will be provided for biometric identification.


Biography

Yi Wang is a Research Assistant Professor with the Department of Computer Science, Hong Kong Baptist University. She received her PhD in Computer Science from RMIT University, Australia, in 2009. From 2009 to 2012, she was a Research Associate with the School of Mathematics and Statistics, The University of New South Wales, Australia. Her research has been largely focused on model-based methods for high-dimensional data anlaysis with applications in biometric identification and eco-statistics. According to ISI Web of Science, since 2007, her work has received more than 510 SCI citations from over 40 countries/territories.


References

  • [Jain et al. 2016] A. K. Jain, K. Nandakumar, A. Ross. "50 years of biometric research: Accomplishments, challenges, and opportunities,” Pattern Recognition Letters, 2016, 79: 80‐105.
  • [Cappelli et al. 2011] R. Cappelli, M. Ferrara, D. Maltoni, "Fingerprint indexing based on minutia cylinder-code,” IEEE Trans. Pattern Anal. Mach. Intell., 2011, 33(5): 1051–1057.
  • [Choi et al. 2012] J. Y. Choi, Y. M. Ro, K. N. Plataniotis. "Color local texture features for color face recognition,” IEEE Trans. Image Processing, 2012, 21(3): 1366‐1380.
  • [Mehrotra et al. 2010] H. Mehrotra, B. Majhi, P. Gupta, "Robust iris indexing scheme using geometric hashing of SIFT keypoints,” J. Netw. Comput. Appl., 2010, 33(3): 300–313.
  • [Lei et al. 2014] Z. Lei, M. Pietikainen, S. Z. Li. "Learning discriminant face descriptor,” IEEE Trans. Pattern Anal. Mach. Intell., 2014, 36(2): 289‐302.
  • [Lu et al. 2015] J. Lu, V. E. Liong, X. Zhou, J. Zhou. "Learning compact binary face descriptor for face recognition”, IEEE Trans. Pattern Anal. Mach. Intell., 2015, 37(10): 2041‐2056.
  • [Wang et al. 2011] Y. Wang, J. Hu. "Global ridge orientation modeling for partial fingerprint identification,” IEEE IEEE Trans. Pattern Anal. Mach. Intell., 2011, 33(1): 72‐87.
  • [He et al. 2015] R. He, Y. Cai, T. Tan, L. Davis, "Learning predictable binary codes for face indexing”, Pattern Recognition, 2015, 48(10): 3160‐3168.
  • [Kan et al. 2016] M. Kan, S. Shan, X. Chen. "Multi‐view deep network for cross‐view classification,” IEEE Conf. Computer Vision and Pattern Recognition (CVPR’16), 2016: 4847-4855.
  • [Wang et al. 2016] D. Wang, C. Otto, A. K. Jain. "Face search at scale,” IEEE Trans. Pattern Anal. Mach. Intell, to appear.
  • [Paliwal et al. 2010] A. Paliwal, U. Jayaraman, P. Gupta. "A score based indexing scheme for palmprint databases,” Intl. Conf. Image Processing (ICIP’10), 2010: 2377‐2380.
  • [Gyaourova et al. 2012] A. Gyaourova, A. Ross. "Index codes for multibiometric pattern retrieval,” IEEE Trans. Inf. Forensics Security, 2012, 7(2): 518‐529.
  • [Rathgeb et al. 2015] C. Rathgeb, F. Breitinger, H. Baier, C. Busch. "Towards Bloom filter‐based indexing of iris biometric data,” Intl. Conf. Biometrics (ICB’15), 2015: 422‐429.
  • [Proenca 2013] H. Proenca. "Iris biometrics: Indexing and retrieving heavily degraded data,” IEEE Trans. Inf. Forensics Security, 2013, 8(12): 1975‐1985.
  • [Wang et al. 2015] Y. Wang, L. Wang, Y. M. Cheung, P. C. Yuen. "Learning compact binary codes for hash‐based fingerprint indexing,” IEEE Trans. Inf. Forensics Security, 2015, 10(8): 1603‐1616.
  • [Yue et al. 2010] F. Yue, B. Li, M. Yu, J. Wang, "Hashing based fast palmprint identification for large‐scale databases,” IEEE Trans. Inf. Forensics Security, 2013, 8(5): 769–778.
  • [Hao et al. 2008] F. Hao, J. Daugman, P. Zielinski, "A fast search algorithm for a large fuzzy database,” IEEE Trans. Inf. Forensics Security, 2008, 3(2): 203–212.
  • [Biggio et al. 2015] B. Biggio, G. Fumera, P. Russu, L. Didaci, F. Roli, "Adversarial biometric recognition: A review on biometric system security from the adversarial machine‐learning perspective,” IEEE Signal Process. Mag., 2015, 32(5): 31—41.
  • [Rane et al. 2013] S. Rane, P. Boufounos, "Privacy‐preserving nearest neighbor methods: Comparing signals without revealing them,” IEEE Signal Process. Mag., 2013, 30(2): 18–28.
Yi Wang

Yi Wang
Hong Kong Baptist University, Hong Kong