Abstract
The tangential neurons in the fly brain are sensitive to the typical optic flow patterns generated during self-motion. In this study, we examine whether a simplified linear model of these neurons can be used to estimate self-motion from the optic flow. We present a theory for the construction of an optimal linear estimator incorporating prior knowledge about the environment. The optimal estimator is tested on a gantry carrying an omnidirectional vision sensor. The experiments show that the proposed approach leads to accurate and robust estimates of rotation rates, whereas translation estimates turn out to be less reliable.
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References
Gibson, J. J. (1950). The perception of the visual world. Houghton Mifflin, Boston.
Hausen, K., Egelhaaf, M. (1989). Neural mechanisms of course control in insects. In: Stavenga, D. C., Hardie, R. C. (eds.), Facets of vision. Springer, Heidelberg, 391–424.
Krapp, H. G., Hengstenberg, B., & Hengstenberg, R. (1998). Dendritic structure and receptive field organization of optic low processing interneurons in the fly. J. of Neurophysiology, 79, 1902–1917.
Franz, M. O. & Krapp, H C. (2000). Wide-field, motion-sensitive neurons and matched filters for optic flow fields. Biol. Cybern., 83, 185–197.
Koenderink, J. J., & van Doorn, A. J. (1987). Facts on optic flow. Biol. Cybern., 56, 247–254.
Chahl, J. S, & Srinivasan, M. V. (1997). Reflective surfaces for panoramic imaging. Applied Optics, 36(31), 8275–8285.
Srinivasan, M. V. (1994). An image-interpolation technique for the computation of optic flow and egomotion. Biol. Cybern., 71, 401–415.
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© 2002 Springer-Verlag Berlin Heidelberg
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Franz, M.O., Chahl, J.S. (2002). Insect-Inspired Estimation of Self-Motion. 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_17
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DOI: https://doi.org/10.1007/3-540-36181-2_17
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