Abstract
The neural control system of a high speed monocular camera head for the tracking of real-world targets is presented in this paper. The tracking system consists of four subsystems: monocular camera head. adaptive image processing system for estimation of the momentary position of object, neural network predictor and PID-controller, controlling motors of the camera head. The designed neural network tracking system performs smooth pursuit of slow objects (50°) with a foveal error less than 0.7° and is able to track objects up to a maximum speed of 320° with foveal error less than 4.5°.
Supported by Federal Ministry for Education, Science, Research, and Technology (BMBF) under grant „Electronic Eye”
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© 1997 Springer-Verlag Berlin Heidelberg
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Ortmann, V., Eckmiller, R. (1997). Neural network visual tracking system. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020255
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DOI: https://doi.org/10.1007/BFb0020255
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