DocumentCode
288893
Title
A unified random field model based neural approach to pixel labeling problems in computer vision
Author
Parthasarathy, Guturu ; Raj, Perugu Ananth
Author_Institution
Dept. of Electron. & Electr. Commun. Eng., Indian Inst. of Technol., Kharagpur, India
Volume
6
fYear
1994
fDate
27 Jun- 2 Jul 1994
Firstpage
4101
Abstract
In this paper, we establish a nexus between the Gibbs random field models and recurrent neural networks and present a unified neural network approach based on this to pixel labeling problems in computer vision. We also present a case study with photometric stereo problem for demonstrating the viability of the present approach
Keywords
Markov processes; computer vision; dynamic programming; recurrent neural nets; stereo image processing; Gibbs random field models; computer vision; photometric stereo imaging; pixel labeling; recurrent neural networks; unified random field model; Computer vision; Degradation; Inverse problems; Labeling; Motion detection; Neural networks; Photometry; Pixel; Recurrent neural networks; Stereo vision;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1901-X
Type
conf
DOI
10.1109/ICNN.1994.374871
Filename
374871
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