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Neural network architecture for 3D object representation

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3 Author(s)
A. -M. Cretu ; Sch. of Inf. Technol. & Eng., Ottawa Univ., Ont., Canada ; E. M. Petriu ; G. G. Patry

The paper discusses a neural network architecture for 3D object modeling. A multi-layered feedforward structure having as inputs the 3D-coordinates of the object points is employed to model the object space. Cascaded with a transformation neural network module, the proposed architecture can be used to generate and train 3D objects, perform transformations, set operations and object morphing. A possible application for object recognition is also presented.

Published in:

Haptic, Audio and Visual Environments and Their Applications, 2003. HAVE 2003. Proceedings. The 2nd IEEE Internatioal Workshop on

Date of Conference:

20-21 Sept. 2003