DocumentCode
328883
Title
Artificial neural network system for 3-D motion perception
Author
Sun, Yi ; Bayoumi, Mohamed M.
Author_Institution
Dept. of Electr. Eng., Queen´´s Univ., Kingston, Ont., Canada
Volume
2
fYear
1993
fDate
25-29 Oct. 1993
Firstpage
1263
Abstract
This paper proposes an artificial neural network system that estimates the 3-D motion and structure parameters of curved surfaces from measured 2-D optical flow parameters. The system is constructed based on the assumption that the optical flow measurement is available and that the object in the scene can be approximated by patches of curved surfaces.
Keywords
image sequences; motion estimation; neural nets; parameter estimation; 3D motion perception; artificial neural network system; curved surfaces; measured 2D optical flow parameters; motion parameter estimation; structure parameter estimation; Artificial neural networks; Fluid flow measurement; Image motion analysis; Motion measurement; Neural networks; Nonlinear optics; Optical computing; Optical fiber networks; Optical imaging; Particle beam optics;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN
0-7803-1421-2
Type
conf
DOI
10.1109/IJCNN.1993.716775
Filename
716775
Link To Document