Applying a Dynamic Recognition Scheme for Vehicle Recognition in Many Object Traffic Scenes
نویسندگان
چکیده
An adaptive object recognition scheme for image sequences of many object scenes is described. The scheme is applied for t r d c object recognition under ego-motion. The recursive estimation of object states is performed by an extended Kalman Filter with modified error estimation, which is a neural network learning process. This new feature allows to separate the judgment needed for selection of best measurement among competitive image segments and the measurement judgment required by the recursive estimator.
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