Skip to main content
SpringerLink
Log in

Learning to Attend — From Bottom-Up to Top-Down

  • Conference paper
Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint (WAPCV 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4840))

Included in the following conference series:

Abstract

The control of overt visual attention relies on an interplay of bottom-up and top-down mechanisms. Purely bottom-up models may provide a reasonable account of the looking behaviors of young infants, but they cannot accurately account for attention orienting of adults in many natural behaviors. But how do humans learn to incorporate top-down mechanisms into their control of attention? The phenomenon of gaze following, i.e. the ability to infer where someone else is looking and to orient to the same location, offers an interesting window into this question. We review findings on the emergence of gaze following in human infants and present a computational model of the underlying learning processes. The model exhibits a gradual incorporation of top-down cues in the infant’s attention control. It explains this process in terms of generic reinforcement learning mechanisms. We conclude that reinforcement learning may be a major driving force behind the incorporation of top-down cues into the control of visual attention.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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.

Similar content being viewed by others

References

  1. Itti, L., Koch, C.: A saliency-based search mechanism for overt and covert shift of visual attention. Vision Research 40, 1489–1506 (2000)

    Article  Google Scholar 

  2. Yarbus, A.L.: Eye movements during perception of complex objects. In: Riggs, L.A. (ed.) Eye Movements and Vision, Ch. VII, pp. 171–196. Plenum Press, New York (1967)

    Chapter  Google Scholar 

  3. Land, M.F., Mennie, N., Rusted, J.: The roles of vision and eye movements in the control of activities of daily living. Perception 28, 1311–1328 (1999)

    Article  Google Scholar 

  4. Land, M.F., Hayhoe, M.M.: In what ways do eye movements contribute to everyday activities? Vision Research 41, 3559–3565 (2001)

    Article  Google Scholar 

  5. Hayhoe, M., Land, M., Shrivastava, A.: Coordination of eye and hand movements in a normal environment. Invest. Ophthalmol & Vis. Sci. 40, S380 (1999)

    Google Scholar 

  6. Wolfe, J.M.: Visual search. In: Pashler, H. (ed.) Attention, University College London Press, London, UK (1998)

    Google Scholar 

  7. Haith, M.M., Hazan, C., Goodman, G.S.: Expectation and anticipation of dynamic visual events by 3.5-month-old babies. Child Development 59, 467–479 (1988)

    Article  Google Scholar 

  8. Dayan, P., Abbott, L.F.: Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. MIT Press, Cambridge, MA, USA (2001)

    MATH  Google Scholar 

  9. Sutton, R.S., Barto, A.G.: Reinforcement Learning. MIT Press, Cambridge, MA (1998)

    Google Scholar 

  10. Scaife, M., Bruner, J.: The capacity for joint visual attention in the infant. Nature 253, 265–266 (1975)

    Article  Google Scholar 

  11. Butterworth, G.E., Cochran, E.: Towards a mechanism of joint visual attention in human infancy. International Journal of Behavioral Development 3, 253–272 (1980)

    Article  Google Scholar 

  12. Butterworth, G.E., Jarrett, N.: What minds have in common is space: Spatial mechanisms serving joint visual attention in infancy. British Journal of Developmental Psychology 9, 55–72 (1991)

    Article  Google Scholar 

  13. Deák, G., Flom, R.A., Pick, A.D.: Effects of Gesture and Target on 12- and 18-Month-Olds’ Joint Visual Attention to Objects in Front of or Behind Them. Developmental Psychology 36, 511–523 (2000)

    Article  Google Scholar 

  14. Brooks, R., Meltzoff, A.N.: The importance of eyes: How infants interpret adult looking behavior. Developmental Psychology 38, 958–966 (2002)

    Article  Google Scholar 

  15. Brooks, R., Meltzoff, A.N.: The development of gaze following and its relation to language. Developmental Science 8, 535–543 (2005)

    Article  Google Scholar 

  16. Meltzoff, A.N., Brooks, R.: Eyes wide shut: The importance of eyes in infant gaze following and understanding of other minds. In: Flom, R., Lee, K., Muir, D. (eds.) Gaze following: Its development and significance, pp. 217–241. Lawrence Erlbaum, Mahwah, NJ (2007)

    Google Scholar 

  17. Mundy, P., Sigman, M., Kasari, C.: A longitudinal study of joint attention and language development in autistic children. Journal of Autism and Developmental Disorders 20, 115–128 (1990)

    Article  Google Scholar 

  18. Treisman, A., Gelade, G.: A feature integration theory of attention. Cognitive Psychology 12, 97–136 (1980)

    Article  Google Scholar 

  19. Brooks, R., Breazeal, C., Marjanovic, M., Scassellati, B., Williamson, M.: The Cog Project: Building a Humanoid Robot. In: Nehaniv, C.L. (ed.) Computation for Metaphors, Analogy, and Agents. LNCS (LNAI), vol. 1562, Springer, Heidelberg (1999)

    Google Scholar 

  20. Kozima, H., Yano, H.: A robot that learns to communicate with human caregivers. In: First International Workshop on Epigenetic Robotics, Lund, Sweden (2001)

    Google Scholar 

  21. Kozima, H.: Infanoid: A babybot that explores the social environment. In: Dautenhahn, K., Bond, A.H., Canamero, L., Edmonds, B. (eds.) Socially Intelligent Agents: Creating Relationships with Computers and Robots, pp. 157–164. Kluwer Academic Publishers, Amsterdam (2002)

    Chapter  Google Scholar 

  22. Nagai, Y., Hosoda, K., Morita, A., Asada, M.: A constructive model for the development of joint attention. Connection Science 15, 211–229 (2003)

    Article  Google Scholar 

  23. Nagai, Y., Asada, M., Hosoda, K.: Learning for joint attention helped by functional development. Advanced Robotics 20(10), 1165–1181 (2006)

    Article  Google Scholar 

  24. Hoffman, M.W., Grimes, D.B., Shon, A.P., Rao., R.P.N.: A probabilistic model of gaze imitation and shared attention. Neural Networks 19, 299–310 (2006)

    Article  MATH  Google Scholar 

  25. Matsuda, G., Omori, T.: Learning of Joint Visual Attention by Reinforcement Learning. In: Altmann, E.M., Cleeremans, A. (eds.) Proceedings of the fourth international conference on cognitive modeling, pp. 157–162. Lawrence Erlbaum Associates, Mahwah, NL (2001)

    Google Scholar 

  26. Triesch, J., Teuscher, C., Deák, G.O., Carlson, E.: Gaze following: why (not) learn it? Developmental Science 9, 125–157 (2006)

    Article  Google Scholar 

  27. Lau, B., Triesch, J.: Learning gaze following in space: a computational model. In: ICDL 2004. 3rd International Conference for Development and Learning, La Jolla, California, USA, pp. 20–22 (October 2004)

    Google Scholar 

  28. Daly, S., Matthews, K., Ribas-Corbera, J.: Visual eccentricity models in face-based video compression. In: IS&SPIE Conference on Human Vision and Electronic Imaging IV, San Jose, California, USA (January 1999)

    Google Scholar 

  29. Stanley, J.C.: Computer simulation of a model of habituation. Nature 261, 146–148 (1976)

    Article  Google Scholar 

  30. Farroni, T., Csibra, G., Simion, F., Johnson, M.H.: Eye contact detection in humans from birth. Proc. Natl. Acad. Sci. USA 99, 9602–9605 (2002)

    Article  Google Scholar 

  31. Li, Z.: Contextual influences in V1 as a basis for pop out and asymmetry in visual search. Proceedings of the National Academy of Sciences 96, 10530–10535 (1999)

    Article  Google Scholar 

  32. Li, Z.: A saliency map in primary visual cortex. Trends in Cognitive Science 6, 9–16 (2002)

    Article  Google Scholar 

  33. von Hofsten, C., Dahlström, E., Fredriksson, Y.: 12-month-old infants’ perception of attention direction in static video images. Infancy 8, 217–231 (2005)

    Article  Google Scholar 

  34. Anstis, S.M., Mayhew, J.W., Morley, T.: The perception of where a face or television ‘portrait’ is looking. American Journal of Psychology 82, 474–489 (1969)

    Article  Google Scholar 

  35. Cline, M.G.: The perception of where a person is looking. American Journal of Psychology 80, 41–50 (1967)

    Article  Google Scholar 

  36. Gibson, J.J., Pick, A.: Perception of another person’s looking behavior. American Journal of Psychology 76, 386–394 (1963)

    Article  Google Scholar 

  37. Jenkins, R., Beaver, J.D., Calder, A.J.: I thought you were looking at me! Direction-specific aftereffects in gaze perception. Psychological Science 17, 506–514 (2006)

    Article  Google Scholar 

  38. Schultz, W., Dayan, P., Montague, P.R.: A neural substrate of prediction and reward. Nature 275, 1593–1599 (1997)

    Google Scholar 

  39. Triesch, J., Jasso, H., Deák, G.O.: Emergency of Mirror Neurons in a Model of Gaze Following. Adaptive Behavior 15, 149–165 (2007)

    Article  Google Scholar 

  40. Fasel, I., Deák, G.O., Triesch, J., Movellan, J.: Combining Embodied Models and Empirical Research for Understanding the Development of Shared Attention. In: ICDL 2002. Proceedings of the International Conference on Development and Learning, Boston, MA, USA (2002)

    Google Scholar 

  41. Johnson, M.H., Dziurawiec, S., Ellis, H.D., Morton, J.: Newborns’ preferential tracking of face-like stimuli and its subsequent decline. Cognition 40, 1–19 (1991)

    Article  Google Scholar 

  42. Valenza, E., Simion, F., Cassia, V.M., Umiltá, C.: Face preference at birth. J. Exp. Psychol. Hum. Percept. Perform 22, 892–903 (1996)

    Article  Google Scholar 

  43. Murray, L., Trevarthen, C.: Emotion regulation of the interactions between two-month-olds and their mothers. In: Field, T., Fox, N. (eds.) Social perception in infants, pp. 89–111. Ablex, Norwood, NJ (1985)

    Google Scholar 

  44. Roberts, S., Pashler, H.: How persuasive is a good fit? A comment on theory testing. Psychological Review 107, 358–367 (2000)

    Article  Google Scholar 

  45. Jasso, H., Triesch, J., Deák, G.O.: A reinforcement learning model explains the development of gaze following. In: ICCM 2006. Proceedings of the 7th International Conference on Cognitive Modeling, Trieste, Italy (2006)

    Google Scholar 

  46. Jasso, H., Triesch, J.: Using eye direction cues for gaze following - a developmental model. In: ICDL 2006. Proceedings of the 5th International Conference on Development and Learning, Bloomington, IN, USA (2006)

    Google Scholar 

  47. Jasso, H.: A reinforcement learning model of gaze following. Unpublished Ph.D. dissertation. University of California, San Diego (2007)

    Google Scholar 

  48. Adrien, J.L., Lenoir, P., Martineau, J., Perrot, A., Hameury, L., Larmande, C., Sauvage, D.: Blind ratings of early symptoms of autism based upon family home movies. Journal of the American Academy of Child and Adolescent Psychiatry 32, 617–626 (1993)

    Article  Google Scholar 

  49. Hutt, C., Ounsted, C.: The biological significance of gaze aversion with particular reference to the syndrome of infantile autism. Behavioral Science 11(5), 346–356 (1966)

    Article  Google Scholar 

  50. Itti, L., Koch, C.: Computational modelling of visual attention. Nature Reviews Neuroscience 2, 194–203 (2001)

    Article  Google Scholar 

  51. Zhaoping, L.: A saliency map in primary visual cortex. Trends in Cognitive Sciences 6, 9–16 (2002)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dept. of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92093, USA

    Hector Jasso

  2. Frankfurt Institute for Advanced Studies, J.W. Goethe University, Frankfurt am Main, Germany

    Jochen Triesch

  3. Dept. of Cognitive Science, University of California, San Diego, La Jolla, CA 92093, USA

    Jochen Triesch

Authors
  1. Hector Jasso
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jochen Triesch
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Joanneum Research, Forschungsgesellschaft mbH, Computational Perception Group,, Institute of Digital Image Processing, Wastiangasse 6, 8010, Graz, Austria

    Lucas Paletta

  2. Autonomous Intelligent Systems (AIS), Autonomous Robots Department, Fraunhofer Institute, Schloss Birlinghoven, 53754, Sankt Augustin, Germany

    Erich Rome

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Jasso, H., Triesch, J. (2007). Learning to Attend — From Bottom-Up to Top-Down. In: Paletta, L., Rome, E. (eds) Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint. WAPCV 2007. Lecture Notes in Computer Science(), vol 4840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77343-6_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-77343-6_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77342-9

  • Online ISBN: 978-3-540-77343-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation