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Towards a Methodology for Retrieving Suspects Using 3D Facial Descriptors

  • Naoufel WerghiEmail author
  • Hassen Drira
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 684)

Abstract

We propose a first investigation towards a methodology for exploiting 3D descriptors in suspect retrieval in the context of crime investigation. In this field, the standard method is to construct a facial composite, based on witness description, by an artist of via software, then search a match for it in legal databases. An alternative or complementary scheme would be to define a system of 3D facial attributes that can fit human verbal face description and use them to annotate face databases. Such framework allows a more efficient search of legal face database and more effective suspect shortlisting. In this paper, we describe some first steps towards that goal, whereby we define some novel 3D face attributes, we analyze their capacity for face categorization though a hieratical clustering analysis. Then we present some experiments, using a cohort of 107 subjects, assessing the extent to which some faces partition based on some of these attributes meets its human-based counterpart. Both the clustering analysis and the experiments results reveal encouraging indicators for this novel proposed scheme.

Keywords

3D face Clustering Face recognition 

References

  1. 1.
    Ben Amor, B., Drira, H., Ballihi, L., Srivastava, A., Daoudi, M., Daoudi, M.: An experimental illustration of 3D facial shape analysis under facial expressions. Annales des Télécommunications 64(5–6), 369–379 (2009)Google Scholar
  2. 2.
    Ben Amor, B., Drira, H., Berretti, S., Daoudi, M., Srivastava, A., Srivastava, A.: 4-D facial expression recognition by learning geometric deformations. IEEE Trans. Cybern. 44(12), 2443–2457 (2014)CrossRefGoogle Scholar
  3. 3.
    Antonopoulos, P., Nikolaidis, N., Pitas, I.: Hierarchical face clustering using sift image features. In Proceedings of the IEEE Symposium on Computational Intelligence in Image and Signal Processing, pp. 325–329 (2007)Google Scholar
  4. 4.
    Secord, A., Lu, J., Finkelstein, A., Singh, M., Nealen, A.: Perceptual models of viewpoint preference. ACM Trans. Graph. 30, 1–13 (2011)CrossRefGoogle Scholar
  5. 5.
    Drira, H., Ben Amor, B., Daoudi, M.M., Srivastava, A.: Pose and expression-invariant 3D face recognition using elastic radial curves. In: British Machine Vision Conference, pp. 1–11 (2010)Google Scholar
  6. 6.
    Drira, H., Ben Amor, B., Srivastava, A., Daoudi, M.: A riemannian analysis of 3D nose shapes for partial human biometrics. In: International Conference on Computer Vision, pp. 2050–2057 (2009)Google Scholar
  7. 7.
    Drira, H., Ben Amor, B., Srivastava, A., Daoudi, M., Slama, R., Slama, R.: 3d face recognition under expressions, occlusions, and pose variations. IEEE Trans. Pattern Anal. Mach. Intell. 35(9), 2270–2283 (2013)CrossRefGoogle Scholar
  8. 8.
    Klare, B.F., et al.: Suspect identification based on descriptive facial attributes. In: Proceedings of the IEEE/IAPR International Joint Conference on Biometrics, pp. 1–8 (2014)Google Scholar
  9. 9.
    Fan, W., Yeung, D.Y.: Face recognition with image sets using hierarchically extracted exemplars from appearance manifold. In: Proceedings of the IEEE 7th International Conference on Automatic Face and Gesture Recognition, pp. 177–192 (2007)Google Scholar
  10. 10.
    Torzanos, F.A.: The points of local nonconvexity of starshaped objects sets. Pac. J. Math. 11, 25–35 (1982)Google Scholar
  11. 11.
    Frowd, C.: Craniofacial identification. In: Wilkinson, C., Rynn, C. (eds.) Craniofacial Identification, pp. 42–56 (2012)Google Scholar
  12. 12.
    Han, H., Klare, B., Bonnen, K.: Matching composite sketches to face photos: a component based approach. IEEE Trans. Inform. Forensics Secur. 8, 191–204 (2013)CrossRefGoogle Scholar
  13. 13.
    Jain, A., Dubes, R.C.: Algorithms for Clustering Data. Prentice- Hall Inc., Upper Saddle River (1988)zbMATHGoogle Scholar
  14. 14.
    Jain, A., Klare, B., Park, U.: Face matching and retrieval in forensics applications. IEEE Multimedia 19, 20–28 (2012)CrossRefGoogle Scholar
  15. 15.
    Klare, B., Li, Z., Jain, A.: Matching forensic sketches to mug shot photos. IEEE Trans. Pattern Anal. Mach. Intell. 33, 639–646 (2011)CrossRefGoogle Scholar
  16. 16.
    Mcquiston, D., Topp, L., Malpass, R.: Use of facial composite systems in us law enforcement agencies. Psychol. Crime Law 12, 505–517 (2006)CrossRefGoogle Scholar
  17. 17.
    Werghi, N.: The 3D facial kernel: Application to facial surface spherical mapping and alignment. In: Proceedings of the IEEE Conference Systems, Men and Cybernetics, pp. 1777–1784 (2010)Google Scholar
  18. 18.
    Savran, A., Alyüz, N., Dibeklioǧlu, H., Çeliktutan, O., Gökberk, B., Sankur, B., Akarun, L.: Bosphorus database for 3D face analysis. In: Proceedings of the First COST 2101 Workshop on Biometrics and Identity Management, May 2008Google Scholar
  19. 19.
    Srivastava, A., Klassen, E., Joshi, S.H., Jermyn, I.H.: Shape analysis of elastic curves in euclidean spaces. IEEE Trans. Pattern Anal. Mach. Intell. 33(7), 1415–1428 (2011)CrossRefGoogle Scholar
  20. 20.
    Wang, X., Tang, X.: Face photo-sketch synthesis and recognition. IEEE Trans. Pattern Anal. Mach. Intell. 31, 1955–1967 (2009)CrossRefGoogle Scholar
  21. 21.
    Xia, B., Ben Amor, B., Drira, H., Daoudi, M., Ballihi, L., Ballihi, L.: Combining face averageness and symmetry for 3d-based gender classification. Pattern Recognit. 48(3), 746–758 (2015)CrossRefGoogle Scholar
  22. 22.
    Yuen, P., Man, C.: Human face image searching system using sketches. IEEE Trans. SMC Part A Syst. Humans 37, 493–504 (2007)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Khalifa UniversityAbu DhabiUAE
  2. 2.Institut Mines-Tlcom/Tlcom Lille, Centre de Recherche en InformatiqueSignal et Automatique de Lille (UMR CNRS 9189)Villeneuve-d’AscqFrance

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