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Spiral Topologies for Biometric Recognition

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Advanced Studies in Biometrics

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3161))

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Abstract

Biometric recognition has attracted the attention of scientists, investors, government agencies as well as the media for the great potential in many application domains. It turns out that there are still a number of intrinsic drawbacks in all biometric techniques. In this paper we postulate the need for a proper data representation which may simplify and augment the discrimination among different instances or biometric samples of different subjects. Considering the design of many natural systems it turns out that spiral (circular) topologies are the best suited to economically store and process data. Among the many developed techniques for biometric recognition, face analysis seems to be the most promising and interesting modality. The ability of the human visual system of analyzing unknown faces, is an example of the amount of information which can be extracted from face images. Nonetheless, there are still many open problems which need to be ”faced” as well. The choice of optimal resolution of the face within the image, face registration and facial feature extraction are still open issues. This not only requires to devise new algorithms but to determine the real potential and limitations of existing techniques. In this paper two different methods for face matching are presented, based on the same similarity measure but on different image representations. The methods are tested with conventional and also new databases, obtained from real subjects in real working environments.

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References

  1. Chellappa, R., Wilson, C.L., Sirohey, S.: Human and machine recognition of faces: A survey. Proceedings of the IEEE 83, 705–740 (1995)

    Article  Google Scholar 

  2. Kanade, T.: Computer recognition of human faces. Birkhauser, Basel and Stuttgart (1977)

    Google Scholar 

  3. Sinha, P., Poggio, T.: I think I know that face.... Nature 384, 404 (1996)

    Article  Google Scholar 

  4. Wiskott, L., Fellous, J.M., Kruger, N., von der Malsburg, C.: Face recognition and gender determination. In: Proceedings Int.l Workshop on Automatic Face and Gesture Recognition, Zurich, Switzerland, pp. 92–97 (1995)

    Google Scholar 

  5. Jain, A.K., Bolle, R., Pankanti, S.: Biometrics, Personal Identification in Networked Society. Kluwer Academic Publishers, Dordrecht (1999)

    Google Scholar 

  6. Wechsler, H., Phillips, P., Bruce, V., Soulie, F., Huang, T. (eds.): Face Recognition. From Theory to Applications. NATO ASI Series F, vol. 163. Springer, Heidelberg

    Google Scholar 

  7. Cottrell, G., Metcalfe, J.: Face, gender and emotion recognition using holons. In: Touretzky, D. (ed.) Advances in Neural Information Processing Systems, vol. 3, pp. 564–571. Morgan Kaufmann, San Mateo (1991)

    Google Scholar 

  8. Belhumeur, P.N., Hespanha, J.P., Kriegman, D.J.: Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. IEEE Trans. on PAMI, PAMI 19(7), 711–720 (1997)

    Google Scholar 

  9. Edwards, G.J., Cootes, T.F., Taylor, C.J.: Face Recognition Using Active Appearance Models. In: Burkhardt, H., Neumann, B. (eds.) ECCV 1998. LNCS, vol. 1407, pp. 581–595. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  10. Brunelli, R., Poggio, T.: Face recognition through geometrical features. In: Proc. of 2nd European Conference on S. Margherita Ligure, pp. 792–800. Springer, Heidelberg (1992)

    Google Scholar 

  11. Mogbaddam, B., Jebara, T., Pentland, A.: Bayesian face recognition. Pattern Recognition 33(11), 1771–1782 (2000)

    Article  Google Scholar 

  12. Feng, G.C., Yuen, P.C., Dai, D.Q.: Human face recognition using pca on wavelet subband. Journal of Electronic Imaging 9(2), 226–233 (2000)

    Article  Google Scholar 

  13. Liu, C., Wechsler, H.: Evolutionary pursuit and its application to face recognition. IEEE Transaction on PAMI 22(6), 570–582 (2000)

    Google Scholar 

  14. Tistarelli, M., Grosso, E.: Active vision-based face authentication. Image and Vision Computing: Special issue on Facial Image Analysis 18(4), 299–314 (2000)

    Google Scholar 

  15. Darwin, C.: The expression of the emotions in man and animals. John Murray, London (1965) (Original work published 1872)

    Google Scholar 

  16. Goren, C., Sarty, M., Wu, P.: Visual following and pattern discrimination of facelike stimuli by newborn infants. Pediatrics 56, 544–549 (1975)

    Google Scholar 

  17. Walton, G.E., Bower, T.G.R.: Newborns form ”prototypes” in less than 1 minute. Psychological Science 4, 203–205 (1993)

    Article  Google Scholar 

  18. Fagan, J.: Infants’ recognition memory for face. Journal of Experimental Child Psychology 14, 453–476 (1972)

    Article  Google Scholar 

  19. de Haan, M., Nelson, C.A.: “Recognition of the mother’s face by 6-month-old infants: A neurobehavioral study”. Child Development 68, 187–210 (1997)

    Article  Google Scholar 

  20. Leonard, C.M., Rolls, E.T., Wilson, F.A.W., Baylis, G.C.: Neurons in the amygdala of the monkey with responses selective for faces. Behavioral Brain Research 15, 159–176 (1985)

    Article  Google Scholar 

  21. Gauthier, I., Tarr, M.J., Anderson, A.W., Skudlarski, P., Gore, J.C.: “Activation of the middle fusiform “face area” increases with expertise in recognizing novel objects”. Nature Neuroscience 2, 568–573 (1999)

    Article  Google Scholar 

  22. Kanwisher, N., McDermott, J., Chun, M.M.: The fusiform face area: A module in human extrastriate cortex specialized for face perception. Journal of Neuroscience 17, 4302–4311 (1997)

    Google Scholar 

  23. McCarthy, G., Puce, A., Gore, J.C., Allison, T.: Facespecific processing in the human fusiform gyrus. Journal of Cognitive Neuroscience 8, 605–610 (1997)

    Article  Google Scholar 

  24. Schultz, R.T., Gauthier, I., Klin, A., Fulbright, R.K., Anderson, A.W., Volkmar, F.R., Skudlarski, P., Lacadie, C., Cohen, D.J., Gore, J.C.: Abnormal ventral temporal cortical activity during face discrimination among individuals with autism and Asperger syndrome. Archives of General Psychiatry 57, 331–340 (2000)

    Article  Google Scholar 

  25. Damasio, A.R., Damasio, J., Van Hoesen, G.W.: Prosopagnosia: Anatomic basis and behavioral mechanisms. Neurology 32, 331–341 (1982)

    Google Scholar 

  26. Nelson, C.A.: The development and neural bases of face recognition. Infant and Child Development 10, 3–18 (2001)

    Article  Google Scholar 

  27. Aggleton, J.P., Burton, M.J., Passingham, R.E.: Cortical and subcortical afferents to the amygdala of the rhesus monkey (Macaca mulatta). Brain Research 190, 347–368 (1980)

    Article  Google Scholar 

  28. Shepherd, J.: Social factors in face recognition. In: Davies, G., Ellis, H., Shepherd, J. (eds.) Perceiving and remembering faces, pp. 55–79. Academic Press, London (1981)

    Google Scholar 

  29. Yarbus, A.L.: Eye movements and vision. Plenum Press, New York (1967)

    Google Scholar 

  30. Nahm, F.K.D., Perret, A., Amaral, D., Albright, T.D.: How do monkeys look at faces? Journal of Cognitive Neuroscience 9, 611–623 (1997)

    Article  Google Scholar 

  31. Haith, M.M., Bergman, T., Moore, M.J.: Eye contact and face scanning in early infancy. Science 198, 853–854 (1979)

    Article  Google Scholar 

  32. Klin, A.: Eye-tracking of social stimuli in adults with autism. In: NICHD Collaborative Program of Excellence in Autism, Yale University, New Haven, CT (May 2001)

    Google Scholar 

  33. Braathen, B., Bartlett, M.S., Littlewort, G., Movellan, J.R.: First Steps Towards Automatic Recognition of Spontaneous Facial Action Units. In: ACM Workshop on Perceptive User Interfaces, Orlando, FL, November 15-16 (2001)

    Google Scholar 

  34. Picard, R.W.: Toward computers that recognize and respond to user emotion. IBM System (39), 3/4 (2000)

    Google Scholar 

  35. Picard, R.W.: Building HAL: Computers that sense, recognize, and respond to human emotion. MIT Media-Lab TR-532. Also in Society of Photo-Optical Instrumentation Engineers. Human Vision and Electronic Imaging VI, part of IS&T/SPIE9s Photonics West (2001)

    Google Scholar 

  36. Ballard, D.H.: Animate vision. Artificial Intelligence 48, 57–86 (1991)

    Article  Google Scholar 

  37. Aloimonos, Y. (ed.): Purposive, qualitative, active vision. CVGIP: Image Understanding, vol. 56 (July 1992) (special issue on qualitative, active vision)

    Google Scholar 

  38. Tistarelli, M.: Active/space-variant object recognition. Image and Vision Computing 13(3), 215–226 (1995)

    Article  Google Scholar 

  39. Schwartz, E.L., Greve, D.N., Bonmassar, G.: Space-variant active vision: definition, overview and examples. Neural Networks 8(7/8), 1297–1308 (1995)

    Article  Google Scholar 

  40. Curcio, C.A., Sloan, K.R., Kalina, R.E., Hendrickson, A.E.: Human photoreceptor topography. J. Comp. Neurol. 292(4), 497–523 (1990)

    Article  Google Scholar 

  41. Sandini, G., Metta, G.: Retina- like sensors: motivations, technology and applications. In: Secomb, T.W., Barth, F., Humphrey, P. (eds.) Sensors and Sensing in Biology and Engineering, Springer, Heidelberg (2002)

    Google Scholar 

  42. Burt, P.J.: Smart sensing in machine vision. In: Machine Vision: Algorithms, Architectures, and Systems, Academic Press, London (1988)

    Google Scholar 

  43. Tong, F., Li, Z.-N.: Reciprocal-wedge transform for space-variant sensing. IEEE Transactions on PAMI 17, 500–511 (1995)

    Google Scholar 

  44. Schwartz, E.L.: Spatial mapping in the primate sensory projection: Analytic structure and relevance to perception. Biological Cybernetics 25, 181–194 (1977)

    Article  Google Scholar 

  45. Fisher, T.E., Juday, R.D.: A programmable video image remapper. In: Proc. of SPIE, vol. 938, pp. 122–128 (1988)

    Google Scholar 

  46. Grosso, E., Tistarelli, M.: Log-polar Stereo for Anthropomorphic Robots. In: Vernon, D. (ed.) ECCV 2000. LNCS, vol. 1842, pp. 299–313. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  47. Sandini, G., Tistarelli, M.: Vision and space-variant sensing. In: Wechsler, H. (ed.) Neural Networks for Perception: Human and Machine Perception, Academic Press, London (1991)

    Google Scholar 

  48. Yeshurun, Y., Schwartz, E.L.: Shape description with a space-variant sensor: Algorithms for scan-path, fusion and convergence over multiple scans. IEEE Transactions on PAMI 11, 1217–1222 (1989)

    Google Scholar 

  49. Daugman, J.: High confidence visual recognition of persons by a test of statistical independence. IEEE Transactions on PAMI 15(11), 1148–1161 (1993)

    Google Scholar 

  50. Bigun, J.: Retinal vision applied to facial features detection and face authentication. Pattern Recognition Letters 23(4), 463–475 (1997)

    Google Scholar 

  51. Jain, K., Prabhakar, S., Hong, L., Pankanti, S.: Filterbank-based fingerprint matching. IEEE Transactions on IP 9(5), 846–859 (2000)

    Article  Google Scholar 

  52. Tistarelli, M., Lagorio, A., Grosso, E.: Understanding Iconic Image-Based Face Biometrics. In: Tistarelli, M., Bigun, J., Jain, A.K. (eds.) ECCV 2002. LNCS, vol. 2359, pp. 19–29. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  53. Tistarelli, M., Lagorio, A., Grosso, E.: Image-Based techniques for biometric authentication. In: Proc. of Int.l Conference on Multimedia and Expo, special session on Biometrics: New Challenges for User Authentification, Lausanne, Switzerland, August 22-26 (2002)

    Google Scholar 

  54. Grother, P.J.: Cross validation comparison of NIST ocr databases. In: Proceedings of the SPIE, vol. 1906, pp. 296–307 (1993)

    Google Scholar 

  55. Samaria, F., Harter, A.: Parameterisation of a Stochastic Model for Human Face Identification. In: Proceedings of 2nd IEEE Workshop on Applications of Computer Vision, Sarasota, FL, IEEE Computer Society Press, Los Alamitos (1994)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Computer Vision Laboratory, University of Sassari, piazza Duomo, 6, 07041, Alghero (SS), Italy

    Massimo Tistarelli & Enrico Grosso

  2. Computer Vision Laboratory, DIST – University of Genova, via Opera Pia, 13, 16145, Genova, Italy

    Andrea Lagorio

Authors
  1. Massimo Tistarelli
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  2. Enrico Grosso
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  3. Andrea Lagorio
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Editors and Affiliations

  1. University of Sassari, 07041, Alghero, Italy

    Massimo Tistarelli

  2. School of Information Science, Computer and Electrical Engineering (IDE), Halmstad University, Box 823, SE-301 18, Halmstad

    Josef Bigun

  3. DEIR - University of Sassari, Sassari, Italy

    Enrico Grosso

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Tistarelli, M., Grosso, E., Lagorio, A. (2005). Spiral Topologies for Biometric Recognition. In: Tistarelli, M., Bigun, J., Grosso, E. (eds) Advanced Studies in Biometrics. Lecture Notes in Computer Science, vol 3161. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11493648_4

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  • DOI: https://doi.org/10.1007/11493648_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26204-6

  • Online ISBN: 978-3-540-28638-7

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