Skip to main content

Ultra-Rapid Scene Categorization with a Wave of Spikes

  • Conference paper
  • First Online:
Biologically Motivated Computer Vision (BMCV 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2525))

Included in the following conference series:

Abstract

Recent experimental work has shown that the primate visual system can analyze complex natural scenes in only 100–150 ms. Such data, when combined with anatomical and physiological knowledge, seriously constrains current models of visual processing. In particular, it suggests that a lot of processing can be achieved using a single feed-forward pass through the visual system, and that each processing layer probably has no more than around 10 ms before the next stage has to respond. In this time, few neurons will have generated more than one spike, ruling out most conventional rate coding models. We have been exploring the possibility of using the fact that strongly activated neurons tend to fire early and that information can be encoded in the order in which a population of cells fire. These ideas have been tested using SpikeNet, a computer program that simulates the activity of very large networks of asynchronously firing neurons. The results have been extremely promising, and we have been able to develop artificial visual systems capable of processing complex natural scenes in real time using standard computer hardware (see http://www.spikenet-technology.com).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Potter, M.C., Meaning in visual search. Science, 187: (1975) 965–6.

    Article  Google Scholar 

  2. Potter, M.C., Short-term conceptual memory for pictures. J Exp Psychol (Hum Learn), 2: (1976) 509–22.

    Article  Google Scholar 

  3. Thorpe, S., Fize, D., Marlot, C., Speed of processing in the human visual system. Nature, 381: (1996) 520–2.

    Article  Google Scholar 

  4. VanRullen, R., Thorpe, S.J., Is it a bird? Is it a plane? Ultra-rapid visual categorisation of natural and artifactual objects. Perception, 30: (2001) 655–68.

    Article  Google Scholar 

  5. Delorme, A., Richard, G., Fabre-Thorpe, M., Ultra-rapid categorisation of natural scenes does not rely on colour cues: a study in monkeys and humans. Vision Res, 40: (2000) 2187–200.

    Article  Google Scholar 

  6. Fabre-Thorpe, M., Delorme, A., Marlot, C., Thorpe, S., A limit to the speed of processing in ultra-rapid visual categorization of novel natural scenes. J Cogn Neurosci, 13: (2001) 171–80.

    Article  Google Scholar 

  7. Thorpe, S.J., Gegenfurtner, K.R., Fabre-Thorpe, M., Bulthoff, H.H., Detection of animals in natural images using far peripheral vision. Eur J Neurosci, 14: (2001) 869–876.

    Article  Google Scholar 

  8. Rousselet, G.A., Fabre-Thorpe, M., Thorpe, S.J., Parallel processing in high level categorisation of natural images. Nature Neuroscience, 5: (2002) 629–30.

    Google Scholar 

  9. Li, F.F., VanRullen, R., Koch, C., Perona, P., Rapid natural scene categorization in the near absence of attention. Proc Natl Acad Sci U S A, 99: (2002) 9596–601.

    Google Scholar 

  10. Thorpe, S.J., Bacon, N., Rousselet, G., Macé, M.J.-M., Fabre-Thorpe, M., Rapid categorisation of natural scenes: feed-forward vs. feedback contribution evaluated by backwards masking. Perception, 31 suppl: (2002) 150.

    Google Scholar 

  11. Fabre-Thorpe, M., Richard, G., Thorpe, S.J., Rapid categorization of natural images by rhesus monkeys. NeuroReport, 9: (1998) 303–308.

    Article  Google Scholar 

  12. Nowak, L.G., Bullier, J., The timing of information transfer in the visual system, in J. Kaas, K. Rockland, and A. Peters, Editors. (eds) Extrastriate cortex in primates, Plenum: New York. (1997) 205–241.

    Chapter  Google Scholar 

  13. Logothetis, N.K., Sheinberg, D.L., Visual object recognition. Annu Rev Neurosci, 19: (1996) 577–621.

    Article  Google Scholar 

  14. Rolls, E.T., Deco, G., Computational Neuroscience of Vision. Oxford: Oxford University Press (2002)

    Google Scholar 

  15. Oram, M.W., Perrett, D.I., Time course of neural responses discriminating different views of the face and head. J Neurophysiol, 68: (1992) 70–84.

    Google Scholar 

  16. Keysers, C., Xiao, D.K., Foldiak, P., Perrett, D.I., The speed of sight. J Cogn Neurosci, 13: (2001) 90–101.

    Article  Google Scholar 

  17. Thorpe, S.J., Imbert, M., Biological constraints on connectionist models., inR. Pfeifer, et al., Editors. (eds) Connectionism in Perspective., Elsevier: Amsterdam. (1989) 63–92.

    Google Scholar 

  18. Thorpe, S., Delorme, A., Van Rullen, R., Spike-based strategies for rapid processing. Neural Networks, 14: (2001) 715–25.

    Article  Google Scholar 

  19. van Rossum, M.C., Turrigiano, G.G., Nelson, S.B., Fast propagation of firing rates through layered networks of noisy neurons. J Neurosci, 22: (2002) 1956–66.

    Google Scholar 

  20. VanRullen, R., Thorpe, S.J., Rate coding versus temporal order coding: what the retinal ganglion cells tell the visual cortex. Neural Comput, 13: (2001) 1255–83.

    Article  MATH  Google Scholar 

  21. Thorpe, S.J., Spike arrival times: A highly efficient coding scheme for neural networks., in R. Eckmiller, G. Hartman, and G. Hauske, Editors. (eds) Parallel processing in neural systems, Elsevier: North-Holland. (1990) 91–94.

    Google Scholar 

  22. Gautrais, J., Thorpe, S., Rate coding versus temporal order coding: a theoretical approach. Biosystems, 48: (1998) 57–65.

    Article  Google Scholar 

  23. Thorpe, S.J., Gautrais, J., Rank Order Coding, in J. Bower, Editor. (eds) Computational Neuroscience: Trends in Research 1998, Plenum Press: New York. (1998) 113–118.

    Chapter  Google Scholar 

  24. VanRullen, R., Gautrais, J., Delorme, A., Thorpe, S., Face processing using one spike per neurone. Biosystems, 48: (1998) 229–39.

    Article  Google Scholar 

  25. Delorme, A., Thorpe, S.J., Face identification using one spike per neuron: resistance to image degradations. Neural Networks, 14: (2001) 795–803.

    Article  Google Scholar 

  26. Giurfa, M., Menzel, R., Insect visual perception: complex abilities of simple nervous systems. Curr Opin Neurobiol, 7: (1997) 505–13.

    Article  Google Scholar 

  27. Troje, N.F., Huber, L., Loidolt, M., Aust, U., Fieder, M., Categorical learning in pigeons: the role of texture and shape in complex static stimuli. Vision Res, 39: (1999) 353–66.

    Article  Google Scholar 

  28. VanRullen, R., Delorme, A., Thorpe, S.J., Feed-forward contour integration in primary visual cortex based on asynchronous spike propagation. Neurocomputing, 38-40: (2001) 1003–1009.

    Google Scholar 

  29. Bullier, J., Integrated model of visual processing. Brain Res Brain Res Rev, 36: (2001) 96–107.

    Article  Google Scholar 

  30. Bullier, J., Hupe, J.M., James, A.C., Girard, P., The role of feedback connections in shaping the responses of visual cortical neurons. Prog Brain Res, 134: (2001) 193–204.

    Article  Google Scholar 

  31. Ullman, S., Vidal-Naquet, M., Sali, E., Visual features of intermediate complexity and their use in classification. Nat Neurosci, 5: (2002) 682–7.

    Google Scholar 

  32. Lamme, V.A., Roelfsema, P.R., The distinct modes of vision offered by feedforward and recurrent processing. Trends Neurosci, 23: (2000) 571–9.

    Article  Google Scholar 

  33. Roelfsema, P.R., Lamme, V.A., Spekreijse, H., Bosch, H., Figure-ground segregation in a recurrent network architecture. J Cogn Neurosci, 14: (2002) 525–37.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Thorpe, S. (2002). Ultra-Rapid Scene Categorization with a Wave of Spikes. In: Bülthoff, H.H., Wallraven, C., Lee, SW., Poggio, T.A. (eds) Biologically Motivated Computer Vision. BMCV 2002. Lecture Notes in Computer Science, vol 2525. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36181-2_1

Download citation

  • DOI: https://doi.org/10.1007/3-540-36181-2_1

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00174-4

  • Online ISBN: 978-3-540-36181-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics