Image interpretation using contextual feedback

Authors:
G. C. Lai;R. J. P. De Figueiredo
Affiliations:
-;-
Venue:
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol.2)-Volume 2 - Volume 2
Year:
1995

Citing 3
Cited 1

Original Contribution: Efficient learning procedures for optimal interpolative nets

Neural Networks
Computer and Robot Vision

Computer and Robot Vision
Computer Vision

Computer Vision

Mumford-Shah regularizer with contextual feedback

Journal of Mathematical Imaging and Vision

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Abstract

We present a methodology for scene analysis using contextual feedback and demonstrate the approach in a simple example. In our approach, we combine bottom-up and top-down decision making into a systematic mechanism. From feedback of high-level descriptions, the system iteratively arrives at improved identification. The implementation uses OINNs (optimal interpolative neural networks) to determine plausibility and enforce constraints in label assignments. The proposed method can be extended for the analysis of more complex scenes.