Abstract
A new approach to real-time machine vision in dynamic scenes is presented based on special hardware and methods for feature extraction and information processing. Using integral spatio-temporal models, it by-passes the nonunique inversion of the perspective projection by applying recursive least squares filtering. By prediction error feedback methods similar to those used in modern control theory, all spatial state variables including the velocity components are estimated. Only the last image of the sequence needs to be evaluated, thereby alleviating the real-time image sequence processing task.
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This research has been partially supported by the German Federal Ministry of Research and Technology (BMFT), the Deutsche Forschungsgemeinschaft (DFG), the Daimler-Benz AG, and by Messerschmitt-Bölkow-Blohm GmbH (MBB).
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Dickmanns, E.D., Graefe, V. Dynamic monocular machine vision. Machine Vis. Apps. 1, 223–240 (1988). https://doi.org/10.1007/BF01212361
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DOI: https://doi.org/10.1007/BF01212361