Motion Vision pp 143-168 | Cite as

Extracting Egomotion from Optic Flow: Limits of Accuracy and Neural Matched Filters

  • Hans-Jürgen Dahmen
  • Mattihas O. Franz
  • Holger G. Krapp
Chapter

Abstract

In this chapter we review two pieces of work aimed at understanding the principal limits of extracting egomotion parameters from optic flow fields (Dahmen et al. 1997) and the functional significance of the receptive field organization of motion sensitive neurones in the fly’s visual system (Franz and Krapp 1999). In the first study, we simulated noisy image flow as it is experienced by an observer moving through an environment of randomly distributed objects for different magnitudes and directions of simultaneous rotation R and translation T. Estimates R’ of the magnitude and direction of R and t’ of the direction of T were derived from samples of this perturbed image flow and were compared with the original vectors using an iterative procedure proposed by Koenderink and van Doom (1987). The sampling was restricted to one or two cone-shaped subregions of the visual field, which had variable angular size and viewing directions oriented either parallel or orthogonal with respect to the egomotion vectors R and T. We also investigated the influence of environmental structure, such as various depth distributions of objects and the role of planar or spherical surfaces. From our results we derive two general rules how to optimize egomotion estimates: (i) Errors are minimized by expanding the field of view. (ii) Sampling image motion from opposite directions improves the accuracy, particularly for small fields of view.

Keywords

Visual Field Receptive Field Optic Flow Matched Filter Angular Separation 
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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References

  1. Blanke H, Varjã D (1995) Visual determination of self motion components: Regionalization of the optomotor response in the backswimmer Notonecta. In: Elsner N, Menzel R (eds) Nervous systems and behaviour. Proc 23rd Göttingen Neurobiol Conf. Thieme, Stuttgart, p 265Google Scholar
  2. Borst A, Egelhaaf M, Haag J (1995) Mechanisms of dendritic integration underlying gain control in fly motion-sensitive interneurons. J Comput Neurosci 2: 5–18PubMedCrossRefGoogle Scholar
  3. Buchner E (1976) Elementary movement detectors in an insect visual system. Biol Cybern 24: 85–101CrossRefGoogle Scholar
  4. Chahl JS, Srinivasan MV (1997) Reflective surfaces for panoramic imaging. Appl Optics 36: 8275–8285CrossRefGoogle Scholar
  5. Dahmen H (1991) Eye specialization in waterstriders: an adaptation to life in a flat world. J Comp Physiol A 169: 623–632CrossRefGoogle Scholar
  6. Dahmen H, Wüst RW, Zeil J (1997) Extracting egomotion parameters from optic flow: principal limits for animals and machines. In: Srinivansan MV, Venkatesh S (eds) From living eyes to seeing machines. Oxford University Press, Oxford, New York, pp 174–198Google Scholar
  7. Egelhaaf M, Borst A (1993) Movement detection in arthropods. In: Miles FA, Wallman J (eds) Visual motion and its role in the stabilization of gaze. Elsevier, Amsterdam, London, pp 53–77Google Scholar
  8. Franz MO, Krapp HG (2000) Wide-field, motion-sensitive neurons and matched filters for optic flow fields. Biol Cybern: in pressGoogle Scholar
  9. Franz MO, Schölkopf B, Mallot HA, Bülthoff HH (1998) Where did I take that snapshot? Scene-based homing by image matching.79: 191–202Google Scholar
  10. Frost B (1993) Subcortical analysis of visual motion: Relative motion, figure-ground discrimination and self induced optic flow. In: Miles FA, Wallman J (eds) Visual motion and its role in the stabilization of gaze. Elsevier, Amsterdam, London, pp 159–175Google Scholar
  11. Gibson JJ (1950) The Perception of the Visual World. Houghton Mifflin, Boston.Google Scholar
  12. Götz KG, Hengstenberg B, Biesinger R (1979) Optomotor control of wing beat and body posture in Drosophila. Biol Cybern 35: 101–112CrossRefGoogle Scholar
  13. Götz KG, Wandel U (1984) Optomotor control of the force of flight in Drosophila and Musca. Biol Cybern 51: 135–139CrossRefGoogle Scholar
  14. Hausen K (1981) Monocular and binocular computation of motion in the lobula plate of the fly. Verh Dtsch Zool Ges 1981: 49–70Google Scholar
  15. Hausen K (1982a) Motion sensitive interneurons in the optomotor system of the fly. I. The horizontal cells: Structure and signals. Biol Cybern 45: 143–156CrossRefGoogle Scholar
  16. Hausen K (1982b) Motion sensitive interneurons in the optomotor system of the fly. II. The horizontal cells: Receptive field organization and response characteristics. Biol Cybem 46: 67–79CrossRefGoogle Scholar
  17. Hausen K (1984) The lobula complex of the fly: structure, function and significance in visual behaviour. In Ali MA(ed) Photoreception and vision in invertebrates. Plenum, New York, London, pp 523–559CrossRefGoogle Scholar
  18. Hausen K (1993) The decoding of retinal image flow in insects. In: Miles FA, Wallman J (eds) Visual motion and its role in the stabilization of gaze. Elsevier, Amsterdam, London, pp 203–235Google Scholar
  19. Hausen K, Egelhaaf M (1989) Neural mechanisms of visual course control in insects. In: Stavenga DG, Hardie RC (eds) Facets of Vision. Springer Verlag, Berlin, Heidelberg, pp 391–424Google Scholar
  20. Heeger DJ, Jepson AD (1992) Subspace methods for recovering rigid motion I: Algorithim and implementaion. Int J Comp Vis 7: 95–117CrossRefGoogle Scholar
  21. Hengstenberg R (1981) Rotatory visual responses of vertical cells in the lobula plate of Calliphora. Verh Dtsch Zool Ges 1981: 180Google Scholar
  22. Hengstenberg R (1982) Common visual response properties of giant vertical cells in the lobula plate of the blowfly Calliphora. J Comp Physiol A 149: 179–193CrossRefGoogle Scholar
  23. Hengstenberg R, Hausen K, Hengstenberg B (1982) The number and structure of giant vertical cells (VS) in the lobula plate of the blowfly Calliphora erythrocephala. J Comp Physiol A 149: 163–177CrossRefGoogle Scholar
  24. Junger W, Dahmen HJ (1991) Response to self-motion in waterstriders: visual discrimination between rotation and translation. J Comp Physiol A 169: 641–646Google Scholar
  25. Kern R, Nalbach HO, Varjã D (1993). Interaction of local movement detectors enhance the detection of rotation. Optokinetic experiments with the rock crab Pachygrapsus marmoratus. Visual Neurosci 10: 643–52CrossRefGoogle Scholar
  26. Koenderink JJ (1986) Optic flow. Vision Res 26: 161–190PubMedCrossRefGoogle Scholar
  27. Koenderink JJ, van Doorn AJ (1987) Facts on optic flow. Biol Cybern 56: 247–54PubMedCrossRefGoogle Scholar
  28. Krapp HG, Hengstenberg R (1996) Estimation of self-motion by optic flow processing in single visual interneurons. Nature 384: 463–466.PubMedCrossRefGoogle Scholar
  29. Krapp HG, Hengstenberg, R (1997) A fast stimulus procedure for determining local receptive field properties of motion-sensitive visual interneurons. Vision Res 37: 225–234PubMedCrossRefGoogle Scholar
  30. Krapp HG, Hengstenberg B, Hengstenberg R (1998) Dendritic structure and receptive-field organization of optic flow processing intemeurons in the fly. J Neurophysiol 79: 1902–1917PubMedGoogle Scholar
  31. Land MF (1997) Visual acuity in insects. Ann Rev Entomol. 42: 147–177CrossRefGoogle Scholar
  32. Lappe M (1999) Neuronal processing of optic flow. Int Rev Neurobiol 44. Academic Press, San DiegoGoogle Scholar
  33. Lappe M, Bremmer F, van den Berg AV (1999) Perception of self-motion from optic flow. Trends Cog Sci 3: 329–336CrossRefGoogle Scholar
  34. Longuet-Higgins HC, Prazdny K (1980) The interpretation of a moving retinal image. Proc Roy Soc Lond B 208: 385–97CrossRefGoogle Scholar
  35. Miles FA, Wallman J (1993) Visual motion and its role in the stabilization of gaze. Elsevier, Amsterdam, London, New York, TokyoGoogle Scholar
  36. Nagle MG, Srinivasan MV, Wilson DL (1997) Image interpolation technique for measurement of egomotion in 6 degrees of freedom. J Opt Soc Am A 14: 3233–3241CrossRefGoogle Scholar
  37. Nalbach H-O (1990) Multisensory control of eye stalk orientation in decapod crustaceans. An ecological approach. J Crust Biol 10: 382–399CrossRefGoogle Scholar
  38. Nalbach H-O, Zeil J, Forzin L (1989) Multisensory control of eye-stalk orientation in space: Crabs from different habitats rely on different senses. J Comp Physiol A 165: 643–649CrossRefGoogle Scholar
  39. Nelson RC, Aloimonos J (1988) Finding motion parameters from spherical motion fields (or the advantage of having eyes in the back of your head). Biol Cybern 58: 261–218PubMedCrossRefGoogle Scholar
  40. Oyster CW, Takahashi ES, Collewijn H. (1972) Directional-selective retinal ganglion cells and control of optokinetic nystagmus in the rabbit. Vision Res 12: 183–193PubMedCrossRefGoogle Scholar
  41. Reichardt W (1987) Evaluation of optical motion information by movement detectors. J Comp Physiol A 161: 533–547PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Hans-Jürgen Dahmen
    • 1
  • Mattihas O. Franz
    • 2
  • Holger G. Krapp
    • 3
  1. 1.Lehrstuhl für Biokybernetik, Biologisches InstitutUniversität TübingenTübingenGermany
  2. 2.DaimlerChrysler AG, Research and TechnologyUlmGermany
  3. 3.Lehrstuhl für NeurobiologieUniversität BielefeldBielefeldGermany

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