Active Vision System for 3d Object Recognition
نویسندگان
چکیده
The authors describe an active 3D object recognition system that can learn complex 3D objects completely unsupervised and that can recognize previously learnt objects from different views. In this paper, we are focussing on a module for the recognition of objects in image sequences. Therefore, we evaluate the optical flow in the sequence and extract a set of invariant features. As a pattern recognizer we suggest the Cellular Neural Network (CNN) architecture and generate an associative memory.The CNN paradigm is considered as a unifying model for spatio-temporal properties of the visual system.
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تاریخ انتشار 1998