Regularization of inverse visual problems involving discontinuities
IEEE Transactions on Pattern Analysis and Machine Intelligence
A methodology for the development of general knowledge-based vision systems
Vision, brain, and cooperative computation
Constraints methods for flexible models
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Graph-Theoretical Methods in Computer Vision
Theoretical Aspects of Computer Science, Advanced Lectures [First Summer School on Theoretical Aspects of Computer Science, Tehran, Iran, July 2000]
Unification as constraint satisfaction in structured connectionist networks
Neural Computation
A novel optimizing network architecture with applications
Neural Computation
Decomposition of two-dimensional shapes for efficient retrieval
Image and Vision Computing
Orthonormal Kernel Kronecker product graph matching
GbRPR'03 Proceedings of the 4th IAPR international conference on Graph based representations in pattern recognition
A structured connectionist unification algorithm
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
Object categorization using bone graphs
Computer Vision and Image Understanding
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We introduce an optimization approach for solving problems in computer vision that involve multiple levels of abstraction. Our objective functions include compositional and specialization hierarchies. We cast vision problems as inexact graph matching problems, formulate graph matching in terms of constrained optimization, and use analog neural networks to perform the optimization. The method is applicable to perceptual grouping and model matching. Preliminary experimental results are shown.