A Correspondence-Based Neural Model for Face Recognition
Chapter
Abstract
In this chapter we develop a correspondence-basedmodel for object recognition.We will focus here on the question how correspondence finding can be realized neurally, using very simple assumptions for the underlying routing structures (amore realistic treatment of these will be given in Chapter 4).
Keywords
Face Recognition Input Image Input Layer Gabor Wavelet Dynamic Link
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References
- Adler, A., Schuckers, M.E.: Comparing human and automatic face recognition performance. IEEE Trans. Syst. Man Cybern B Cybern. 37(5), 1248–1255 (2007)CrossRefGoogle Scholar
- Amaral, D.G., Schumann, C.M., Nordahl, C.W.: Neuroanatomy of autism. Trends Neurosci. 31, 137–145 (2008)CrossRefGoogle Scholar
- Bar, M., Biederman, I.: Localizing the cortical region mediating visual awareness of object identity. In: PNAS, vol. 96, pp. 1790–1799 (1999)Google Scholar
- Biederman, I.: Recognition-by-components: a theory of human image understanding. Psychol. Rev. 94(2), 115–147 (1987)CrossRefGoogle Scholar
- Biederman, I., Kalocsai, P.: Neurocomputational bases of object and face recognition. Phil. Trans. Roy. Soc. B 352, 1203–1219 (1997)CrossRefGoogle Scholar
- Bienenstock, E., von der Malsburg, C.: A neural network for invariant pattern recognition. Europhysics Letters 4(1), 121–126 (1987)CrossRefGoogle Scholar
- Buxhoeveden, D.P., Casanova, M.F.: The minicolumn hypothesis in neuroscience. Brain 125, 935–951 (2002)CrossRefGoogle Scholar
- Cox, D., Meier, P., Oertelt, N., DiCarlo, J.J.: ’breaking’ position-invariant object recognition. Nature Neuroscience 8(9), 1145–1147 (2005)CrossRefGoogle Scholar
- Dantzker, J.L., Callaway, E.M.: Laminar sources of synaptic input to cortical inhibitory interneurons and pyramidal neurons. Nature Neuroscience 3(7), 701–707 (2000)CrossRefGoogle Scholar
- Daugman, J.G.: Two-dimensional spectral analysis of cortical receptive field profiles. Vision Research 20, 847–856 (1980)CrossRefGoogle Scholar
- Dayan, P., Hinton, G.E., Neal, R.M., Zemel, R.S.: The helmholtz machine. Neural Computation 7(5), 889–904 (1995)CrossRefGoogle Scholar
- Deco, G., Rolls, E.T.: A neurodynamical cortical model of visual attention and invariant object recognition. Vision Research 44(6), 621–642 (2004)CrossRefGoogle Scholar
- DeFelipe, J., Hendry, M.C., Jones, E.G.: Synapses of double bouquet cells in monkey cerebral cortex. Brain Research 503, 49–54 (1989)CrossRefGoogle Scholar
- Douglas, R.J., Martin, K.A.: Neuronal circuits of the neocortex. Annual Review of Neuroscience 27, 419–451 (2004)CrossRefGoogle Scholar
- Douglas, R.J., Martin, K.A., Witteridge, D.: A canonical microcircuit for neocortex. Neural Computation 1, 480–488 (1989)CrossRefGoogle Scholar
- Duncan, J.: Selective attention and the organization of visual information. J Exp. Psychol. Gen. 113, 501–517 (1984)CrossRefGoogle Scholar
- Eigen, M.: Selforganization of matter and the evolution of biological macromolecules. Naturwissenschaften 58, 465–523 (1971)CrossRefGoogle Scholar
- Favorov, O.V., Diamond, M.: Demonstration of discrete place-defined columns, segregates, in cat SI. Journal of Comparative Neurology 298, 97–112 (1990)CrossRefGoogle Scholar
- Favorov, O.V., Kelly, D.G.: Minicolumnar organization within somatosensory cortical segregates II. Cerebral Cortex 4, 428–442 (1994)CrossRefGoogle Scholar
- Fiser, J., Biederman, I.: Invariance of long-term visual priming to scale, reflection, translation, and hemisphere. Vision Research 41, 221–234 (2001)CrossRefGoogle Scholar
- Gauthier, I., Skudlarski, P., Gore, J.C., Anderson, A.W.: Expertise for cars and birds recruits brain areas involved in face recognition. Nature Neuroscience 3(2), 191–197 (2000), http://dx.doi.org/10.1038/72140 CrossRefGoogle Scholar
- Gerstner, W.: Population dynamics of spiking neurons: fast transients, asynchronous states, and locking. Neural Computation 12(1), 43–89 (2000)CrossRefGoogle Scholar
- Goldstein, A., Harmon, L., Lesk, A.: Identification of human faces. Proceedings of the IEEE 59, 748–760 (1971)CrossRefGoogle Scholar
- Hubel, D.H., Wiesel, T.N.: Functional architecture of macaque visual cortex. In: Proceedings of the Royal Society of London - B, vol. 198, pp. 1–59 (1977)Google Scholar
- Humphreys, G., Heinke, D.: Spatial representation and selection in the brain: Neuropsychological and computational constraints. Visual cognition 5, 9–47 (1998)CrossRefGoogle Scholar
- Hung, C.P., Kreiman, G., Poggio, T., DiCarlo, J.J.: Fast readout of object identity from macaque inferior temporal cortex. Science 310(5749), 863–866 (2005), http://dx.doi.org/10.1126/science.1117593 CrossRefGoogle Scholar
- Jones, E.G.: Microcolumns in the cerebral cortex. Proceedings of the National Academy of Sciences, USA 97, 5019–5021 (2000)CrossRefGoogle Scholar
- Jones, J., Palmer, L.: An evaluation of the two-dimensional gabor filter model of simple receptive fields in cat striate cortex. Journal of Neurophysiology 58, 1233–1258 (1987)Google Scholar
- Kanwisher, N.: Neuroscience. what’s in a face? Science 311(5761), 617–618 (2006), http://dx.doi.org/10.1126/science.1123983 CrossRefGoogle Scholar
- Kanwisher, N., Yovel, G.: The fusiform face area: a cortical region specialized for the perception of faces. Phil. Trans. R. Soc. B 361, 2109–2128 (2006)CrossRefGoogle Scholar
- Kirkpatrick, S., Gelatt, C.D., Vecchi, M.P.: Optimization by simulated annealing. Science 220(4598), 671–680 (1983), citeseer.ist.psu.edu/kirkpatrick83optimization.html CrossRefMathSciNetGoogle Scholar
- Körner, E., Gewaltig, M.-O., Körner, U., Richter, A., Rodemann, T.: A model of computation in neocortical architecture. Neural Networks 12, 989–1005 (1999)CrossRefGoogle Scholar
- Lades, M., Vorbrüggen, J., Buhmann, J., Lange, J., von der Malsburg, C., Würtz, R., Konen, W.: Distortion invariant object recognition in the dynamic link architecture. IEEE Transactions on computers 42, 300–311 (1993)CrossRefGoogle Scholar
- Luck, S.J., Chelazzi, L., Hillyard, S.A., Desimone, R.: Neural mechanisms of spatial selective attention in areas V1, V2, and V4 of macaque visual cortex. J Neurophysiol. 77(1), 24–42 (1997)Google Scholar
- Lücke, J., Keck, C., von der Malsburg, C.: Rapid convergence to feature layer correspondences. Neural Computation 20(10), 2441–2463 (2008)MATHCrossRefMathSciNetGoogle Scholar
- Lücke, J., von der Malsburg, C.: Rapid processing and unsupervised learning in a model of the cortical macrocolumn. Neural Computation 16, 501–533 (2004)MATHCrossRefGoogle Scholar
- Martinez, A., Benavente, R.: The AR face database, Technical Report 24, CVC (1998)Google Scholar
- Messer, K., Kittler, J., Sadeghi, M., Hamouz, M., Kostin, A., Cardinaux, F., Marcel, S., Bengio, S., Sanderson, C., Poh, N., Rodriguez, Y., Czyz, J., Vandendorpe, L., McCool, C., Lowther, S., Sridharan, S., Chandran, V., Palacios, R.P., Vidal, E., Bai, L., Shen, L., Wang, Y., Yueh-Hsuan, C., Hsien-Chang, L., Yi-Ping, H., Heinrichs, A., Müller, M., Tewes, A., von der Malsburg, C., Würtz, R., Wang, Z., Xue, F., Ma, Y., Yang, Q., Fang, C., Ding, X., Lucey, S., Goss, R., Schneiderman, H.: Face authentication test on the BANCA database. In: Proceedings of the International Conference on Pattern Recognition, Cambridge, vol. 4, pp. 523–532 (2004)Google Scholar
- Mountcastle, V.B.: The columnar organization of the neocortex. Brain 120, 701–722 (1997)CrossRefGoogle Scholar
- Mountcastle, V.B.: Introduction (to a special issue on cortical columns). Cerebral Cortex 13, 2–4 (2003)CrossRefGoogle Scholar
- Muresan, R.C., Savin, C.: Resonance or integration? Self-sustained dynamics and excitability of neural microcircuits. Journal of Neurophysiology 97, 1911–1930 (2007)CrossRefGoogle Scholar
- Murray, J.F., Kreutz-Delgado, K.: Visual recognition and inference using dynamic overcomplete sparse learning. Neural Computation 19(9), 2301–2352 (2007), http://dx.doi.org/10.1162/neco.2007.19.9.2301 MATHCrossRefMathSciNetGoogle Scholar
- Nakayama, K., Silverman, G.H.: Serial and parallel processing of visual feature conjunctions. Nature 320(6059), 264–265 (1986), http://dx.doi.org/10.1038/320264a0 CrossRefGoogle Scholar
- Olshausen, B.A., Anderson, C.H., van Essen, D.C.: A neurobiological model of visual attention and invariant pattern recognition based on dynamic routing of information. Journal of Neuroscience 13(11), 4700–4719 (1993)Google Scholar
- Olshausen, B.A., Field, D.J.: Sparse coding with an overcomplete basis set: a strategy employed by v1? Vision Research 37, 3311–3325 (1997)CrossRefGoogle Scholar
- Peters, A., Cifuentes, J.M., Sethares, C.: The organization of pyramidal cells in area 18 of the rhesus monkey. Cerebral Cortex 7, 405–421 (1997)CrossRefGoogle Scholar
- Peters, A., Yilmaz, E.: Neuronal organization in area 17 of cat visual cortex. Cerebral Cortex 3, 49–68 (1993)CrossRefGoogle Scholar
- Phillips, P., Flynnand, P., Scruggs, T., Bowyer, K., Chang, J., Hoffman, K., Marques, J., Min, J., Worek, W.: Overview of the face recognition grand challenge. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 947–954 (2005)Google Scholar
- Phillips, P.J., Wechsler, H., Huang, J., Rauss, P.J.: The FERET database and evaluation procedure for face recognition algorithms. Image and Vision Computing 16(5), 295–306 (1998)CrossRefGoogle Scholar
- Phillips, P., Moon, H., Rizvi, S., Rauss, P.: The FERET evaluation methodology for face-recognition algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(10), 1090–1104 (2000)CrossRefGoogle Scholar
- Ringach, D.L.: Spatial structure and symmetry of simple-cell receptive fields in macaque primary visual cortex. Journal of Neurophysiology 88, 455–463 (2002)Google Scholar
- Rockland, K.S., Ichinohe, N.: Some thoughts on cortical minicolumns. Experimental Brain Research 158, 265–277 (2004)CrossRefGoogle Scholar
- Sato, Y.D., Wolff, C., Wolfrum, P., von der Malsburg, C.: Dynamic link matching between feature columns for different scale and orientation. In: Ishikawa, M., Doya, K., Miyamoto, H., Yamakawa, T. (eds.) ICONIP 2007, Part I. LNCS, vol. 4984, pp. 385–394. Springer, Heidelberg (2008)CrossRefGoogle Scholar
- Simons, D., Rensink, R.: Change blindness: past, present, and future. Trends Cogn. Sci (Regul. Ed.) 9, 16–20 (2005)CrossRefGoogle Scholar
- Singer, W.: Synchronization, binding and expectancy. In: Arbib, M. (ed.) The handbook of brain theory and neural networks, pp. 1136–1143. MIT Press, Cambridge (2003)Google Scholar
- Summerfield, C., Egner, T., Greene, M., Koechlin, E., Mangels, J., Hirsch, J.: Predictive codes for forthcoming perception in the frontal cortex. Science 314(5803), 1311–1314 (2006)CrossRefGoogle Scholar
- Tan, X., Chen, S., Zhou, Z.-H., Zhang, F.: Recognizing partially occluded, expression variant faces from single training image per person with SOM and soft kNN ensemble. IEEE Transactions on Neural Networks 16(4), 875–886 (2005)CrossRefGoogle Scholar
- Tanaka, K.: Inferotemporal cortex and object vision. Annu. Rev. Neurosci. 19, 109–139 (1996)CrossRefGoogle Scholar
- Tanaka, K.: Columns for complex visual object features in the inferotemporal cortex: clustering of cells with similar but slightly different stimulus selectivities. Cereb. Cortex 13(1), 90–99 (2003)CrossRefGoogle Scholar
- Tarr, M.J., Gauthier, I.: Ffa: a flexible fusiform area for subordinate-level visual processing automatized by expertise. Nature Neuroscience 3(8), 764–769 (2000), http://dx.doi.org/10.1038/77666 CrossRefGoogle Scholar
- Thornton, T.L., Gilden, D.L.: Parallel and serial processes in visual search. Psychol. Rev. 114(1), 71–103 (2007)CrossRefGoogle Scholar
- Treisman, A., Sato, S.: Conjunction search revisited. J Exp. Psychol. Hum. Percept Perform 16(3), 459–478 (1990)CrossRefGoogle Scholar
- Troncoso, E., Muller, D., Korodi, K., Steimer, T., Welker, E., Kiss, J.Z.: Recovery of evoked potentials, metabolic activity and behavior in a mouse model of somatosensory cortex lesion: role of the neural cell adhesion molecule (ncam). Cereb Cortex 14(3), 332–341 (2004)CrossRefGoogle Scholar
- Tsao, D.Y., Freiwald, W.A., Tootell, R.B.H., Livingstone, M.S.: A cortical region consisting entirely of face-selective cells. Science 311, 670–674 (2006)CrossRefGoogle Scholar
- van Vreeswijk, C., Sompolinsky, H.: Chaotic balanced state in a model of cortical circuits. Neural Computation 10, 1321–1372 (1998)CrossRefGoogle Scholar
- Weber, C., Wermter, S.: A self-organizing map of sigma-pi units. Neurocomputing 70(13-15), 2552–2560 (2007)CrossRefGoogle Scholar
- Wilson, H.R., Cowan, J.D.: A mathematical theory of the functional dynamics of cortical and thalamic nervous tissue. Kybernetik 13, 55–80 (1973)CrossRefGoogle Scholar
- Wiskott, L.: The role of topographical constraints in face recognition. Pattern Recognition Letters 20(1), 89–96 (1999)MATHCrossRefGoogle Scholar
- Wiskott, L., Fellous, J.-M., Krüger, N., von der Malsburg, C.: Face recognition by elastic bunch graph matching. IEEE Trans. on Pattern Analysis and Machine Intelligence 19(7), 775–779 (1997), http://www.cnl.salk.edu/~wiskott/Abstracts/WisFelKrue97a.html CrossRefGoogle Scholar
- Wiskott, L., von der Malsburg, C.: Face recognition by dynamic link matching. In: Sirosh, J., Miikkulainen, R., Choe, Y. (eds.) Lateral Interactions in the Cortex: Structure and Function, Austin, TX. The UTCS Neural Networks Research Group, vol. 11, Electronic book (1996), www.cs.utexas.edu/users/nn/web-pubs/htmlbook96/, http://www.cnl.salk.edu/~wiskott/Abstracts/WisMal96c.html ISBN 0-9647060-0-8
- Wolfrum, P., Lücke, J., von der Malsburg, C.: Invariant face recognition in a network of cortical columns. Proc. International Conference on Computer Vision Theory and Applications 2, 38–45 (2008)Google Scholar
- Wolfrum, P., von der Malsburg, C.: Attentional processes in correspondence-based object recognition. In: Proc. COSYNE, p. 330 (2008)Google Scholar
- Wolfrum, P., Wolff, C., Lücke, J., von der Malsburg, C.: A recurrent dynamic model for correspondence-based face recognition. J. Vis. 8(7), 1–18 (2008), http://journalofvision.org/8/7/34/ CrossRefGoogle Scholar
- Wundrich, I.J., von der Malsburg, C., Würtz, R.P.: Image representation by complex cell responses. Neural Computation 16(12), 2563–2575 (2004), http://dx.doi.org/10.1162/0899766042321760 MATHCrossRefGoogle Scholar
- Würtz, R.P.: Multilayer Dynamic Link Networks for Establishing Image Point Correspondences and Visual Object Recognition, Verlag Harri Deutsch, Thun, Frankfurt am Main (1995)Google Scholar
- Yoshimura, Y., Dantzker, J.L.M., Callaway, E.M.: Excitatory cortical neurons form fine-scale functional networks. Nature 433(7028), 868–873 (2005)CrossRefGoogle Scholar
- Yuille, A., Kersten, D.: Vision as Bayesian inference: analysis by synthesis? Trends in Cognitive Sciences 10(7), 301–308 (2006)CrossRefGoogle Scholar
- Zhao, W., Chellappa, R., Phillips, P.J., Rosenfeld, A.: Face recognition: A literature survey. ACM Computing Surveys 53(4), 399–458 (2003)CrossRefGoogle Scholar
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