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Abstract: The
3D tracking problem based on multi visual sensor systems is dealt with ,
of which one sensor that has low resolution and large field of view is
responsible for the control of the global tracking and the other sensor,
which controls the local tracking, has low resolution and small field of
view .A visual Jacobian mapping from task space to vision space is
developed to establish the visual servoing control equation that is used
to predict the future location of the imaged object. By doing that the
region of image to be processed is reduced and the processing speed is
improved . Meanwhile a HCMAC neural network is fabricated to replace the
complex calculation of the inverse Jacobian mapping. Simulation results
show that the speed of image processing and the precision of tracking
are improved by these measures.
Key words:Global-local 3D
tracking Visual Jacobian mapping Servoing Prediction HCMAC
neural network
CLC No: TP24
国家自然科学基金资助项目(59990470). Received 20020122, received in revised form
20020520 |