Revisiting Algorithmic Lateral Inhibition and Accumulative Computation

  • Antonio Fernández-Caballero
  • María T. López
  • Miguel A. Fernández
  • José M. López-Valles
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5601)


Certainly, one of the prominent ideas of Professor Mira was that it is absolutely mandatory to specify the mechanisms and/or processes underlying each task and inference mentioned in an architecture in order to make operational that architecture. The conjecture of the last fifteen years of joint research of Professor Mira and our team at University of Castilla-La Mancha has been that any bottom-up organization may be made operational using two biologically inspired methods called “algorithmic lateral inhibition”, a generalization of lateral inhibition anatomical circuits, and “accumulative computation”, a working memory related to the temporal evolution of the membrane potential. This paper is dedicated to the computational formulations of both methods, which have led to quite efficient solutions of problems related to motion-based computer vision.


Visual Attention Lateral Inhibition Physical Level Selective Visual Attention Inferential Scheme 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    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
  2. 2.
    Deco, G., Rolls, E.T.: Short-term memory, and action selection: A unifying theory. Progress in Neurobiology 76(4), 236–256 (2005)CrossRefGoogle Scholar
  3. 3.
    Delgado, A.E., Mira, J., Moreno-DÍaz, R.: A neurocybernetic model of modal co-operative decision in the Kilmer-McCulloch space. Kybernetes 18(3), 48–57 (1989)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Delgado, A.E., Mira, J.: Algorithmic lateral inhibition as a generic method for visual information processing with potential applications in robotics. Computational Intelligent Systems for Applied Research, 477–484 (2002)Google Scholar
  5. 5.
    Fernández, M.A.: Una arquitectura modular de inspiración biológica con capacidad de aprendizaje para el análisis de movimiento en secuencias de imagen en tiempo real, PhD Thesis, UNED, Madrid, Spain (1995)Google Scholar
  6. 6.
    Fernández, M.A., Mira, J., López, M.T., Alvarez, J.R., Manjarrés, A., Barro, S.: Local accumulation of persistent activity at synaptic level: Application to motion analysis. In: Sandoval, F., Mira, J. (eds.) IWANN 1995. LNCS, vol. 930, pp. 137–143. Springer, Heidelberg (1995)CrossRefGoogle Scholar
  7. 7.
    Fernández, M.A., Fernández-Caballero, A., López, M.T., Mira, J.: Length-Speed Ratio (LSR) as a characteristic for moving elements real-time classification. Real-Time Imaging 9(1), 49–59 (2003)CrossRefGoogle Scholar
  8. 8.
    Fernández-Caballero, A.: Modelos de interacción lateral en computación acumulativa para la obtención de siluetas, PhD Thesis, UNED, Madrid, Spain (2001)Google Scholar
  9. 9.
    Fernández-Caballero, A., Mira, J., Fernández, M.A., López, M.T.: Segmentation from motion of non-rigid objects by neuronal lateral interaction. Pattern Recognition Letters 22(14), 1517–1524 (2001)CrossRefMATHGoogle Scholar
  10. 10.
    Fernández-Caballero, A., Mira, J., Fernández, M.A., Delgado, A.E.: On motion detection through a multi-layer neural network architecture. Neural Networks 16(2), 205–222 (2003)CrossRefGoogle Scholar
  11. 11.
    Fernández-Caballero, A., Mira, J., Delgado, A.E., Fernández, M.A.: Lateral interaction in accumulative computation: A model for motion detection. Neurocomputing 50, 341–364 (2003)CrossRefMATHGoogle Scholar
  12. 12.
    Fernández-Caballero, A., Fernández, M.A., Mira, J., Delgado, A.E.: Spatio-temporal shape building from image sequences using lateral interaction in accumulative computation. Pattern Recognition 36(5), 1131–1142 (2003)CrossRefMATHGoogle Scholar
  13. 13.
    Heinke, D., Humphreys, G.W.: Computational models of visual selective attention: A review. Connectionist Models in Cognitive Psychology 1(4), 273–312 (2005)Google Scholar
  14. 14.
    Heinke, D., Humphreys, G.W., Tweed, C.L.: Top-down guidance of visual search: A computational account. Visual Cognition 14(4-8), 985–1005 (2006)CrossRefGoogle Scholar
  15. 15.
    López, M.T.: Modelado computacional de los mecanismos de atención selectiva mediante redes de interacción lateral, PhD Thesis, UNED, Madrid, Spain (2004)Google Scholar
  16. 16.
    López, M.T., Fernández-Caballero, A., Mira, J., Delgado, A.E., Fernández, M.A.: Algorithmic lateral inhibition method in dynamic and selective visual attention task: Application to moving objects detection and labeling. Expert Systems with Applications 31(3), 570–594 (2006)CrossRefGoogle Scholar
  17. 17.
    López, M.T., Fernández-Caballero, A., Fernández, M.A., Mira, J., Delgado, A.E.: Motion features to enhance scene segmentation in active visual attention. Pattern Recognition Letters 27(5), 469–478 (2006)CrossRefGoogle Scholar
  18. 18.
    López, M.T., Fernández-Caballero, A., Fernández, M.A., Mira, J., Delgado, A.E.: Visual surveillance by dynamic visual attention method. Pattern Recognition 39(11), 2194–2211 (2006)CrossRefGoogle Scholar
  19. 19.
    López, M.T., Fernández-Caballero, A., Fernández, M.A., Mira, J., Delgado, A.E.: Dynamic visual attention model in image sequences. Image and Vision Computing 25(5), 597–613 (2007)CrossRefGoogle Scholar
  20. 20.
    López-Valles, J.M.: Estereopsis y movimiento. Modelo de disparidad de carga: Un enfoque con inspiración biológica, PhD Thesis, Universidad de Castilla-La Mancha, Albacete, Spain (2004)Google Scholar
  21. 21.
    López-Valles, J.M., Fernández, M.A., Fernández-Caballero, A., López, M.T., Mira, J., Delgado, A.E.: Motion-based stereovision model with potential utility in robot navigation. In: Ali, M., Esposito, F. (eds.) IEA/AIE 2005. LNCS, vol. 3533, pp. 16–25. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  22. 22.
    López-Valles, J.M., Fernández, M.A., Fernández-Caballero, A.: Stereovision depth analysis by two-dimensional motion charge memories. Pattern Recognition Letters 28(1), 20–30 (2007)CrossRefGoogle Scholar
  23. 23.
    Marr, D.: Vision. A Computational Investigation into the Human Representation and Processing of Visual Information. W.H. Freeman and Company, New York (1982)Google Scholar
  24. 24.
    Mira, J., Delgado, A.E.: What can we compute with lateral inhibition circuits? In: Mira, J., Prieto, A.G. (eds.) IWANN 2001. LNCS, vol. 2084, pp. 38–46. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  25. 25.
    Mira, J., Fernández, M.A., López, M.T., Delgado, A.E., Fernández-Caballero, A.: A model of neural inspiration for local accumulative computation. In: Moreno-Díaz Jr., R., Pichler, F. (eds.) EUROCAST 2003. LNCS, vol. 2809, pp. 427–435. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  26. 26.
    Mira, J., Delgado, A.E., Fernández-Caballero, A., Fernández, M.A.: Knowledge modelling for the motion detection task: The algorithmic lateral inhibition method. Expert Systems with Applications 27(2), 169–185 (2004)CrossRefGoogle Scholar
  27. 27.
    Mira, J., Delgado, A.E.: On how the computational paradigm can help us to model and interpret the neural function. Natural Computing 6(3), 207–209 (2006)MathSciNetCrossRefGoogle Scholar
  28. 28.
    Mira, J.: The Semantic Gap, Preface of Bio-inspired Modeling of Cognitive Tasks. In: IWINAC 2007. LNCS, vol. 4528. Springer, Heidelberg (2007)Google Scholar
  29. 29.
    Mira, J.: Symbols versus connections: 50 years of artificial intelligence. Neurocomputing 71(4-6), 671–680 (2008)CrossRefGoogle Scholar
  30. 30.
    Newell, A.: The Knowledge Level. AI Magazine, 1–20 (Summer 1981)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Antonio Fernández-Caballero
    • 1
    • 3
  • María T. López
    • 2
    • 3
  • Miguel A. Fernández
    • 2
    • 3
  • José M. López-Valles
    • 1
  1. 1.Universidad de Castilla-La Mancha Escuela de Ingenieros Industriales de AlbaceteAlbaceteSpain
  2. 2.Universidad de Castilla-La Mancha Escuela Superior de Ingeniería InformáticaAlbaceteSpain
  3. 3.Instituto de Investigación en Informática de AlbaceteAlbaceteSpain

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