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Weighting Elementary Movement Detectors Tuned to Different Temporal Frequencies to Estimate Image Velocity

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Biomimetic and Biohybrid Systems (Living Machines 2023)

Abstract

Insects’ ability to know the velocity they are flying is of interest to both biologists and roboticists. While the Reichardt detector is one of the most prominent models for insect motion vision, it has various limitations when extracting image velocity in a natural environment. Here we demonstrate a method for estimating image velocity by weighting the outputs of a population of Reichardt detectors where individual detectors are tuned to different temporal frequencies. By providing stimuli of different spatial frequencies and velocities, we then perform a convex optimisation on each average output to find weights. We show that when the weighted detector arrays are provided with different stimuli, the output reasonably approximates image velocity. Our results have implications for power-limited autonomous systems and suggest a potential mechanism for insect motion vision.

Supported by the Defence Science and Technology Laboratory (DSTLX1000161145).

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Correspondence to Benjamin P. Campbell .

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Campbell, B.P., Lin, HT., Krapp, H.G. (2023). Weighting Elementary Movement Detectors Tuned to Different Temporal Frequencies to Estimate Image Velocity. In: Meder, F., Hunt, A., Margheri, L., Mura, A., Mazzolai, B. (eds) Biomimetic and Biohybrid Systems. Living Machines 2023. Lecture Notes in Computer Science(), vol 14157. Springer, Cham. https://doi.org/10.1007/978-3-031-38857-6_29

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  • DOI: https://doi.org/10.1007/978-3-031-38857-6_29

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