Learning Probabilistic Models for Contour Completion in Natural Images
- 18 October 2007
- journal article
- Published by Springer Science and Business Media LLC in International Journal of Computer Vision
- Vol. 77 (1), 47-63
- https://doi.org/10.1007/s11263-007-0092-6
Abstract
No abstract availableKeywords
This publication has 42 references indexed in Scilit:
- Learning to detect natural image boundaries using local brightness, color, and texture cuesIeee Transactions On Pattern Analysis and Machine Intelligence, 2004
- Shape matching and object recognition using shape contextsIeee Transactions On Pattern Analysis and Machine Intelligence, 2002
- Globally optimal regions and boundaries as minimum ratio weight cyclesIeee Transactions On Pattern Analysis and Machine Intelligence, 2001
- Orientation, Scale, and Discontinuity as Emergent Properties of Illusory Contour ShapeNeural Computation, 2001
- Factor graphs and the sum-product algorithmIEEE Transactions on Information Theory, 2001
- Correctness of Local Probability Propagation in Graphical Models with LoopsNeural Computation, 2000
- Completion energies and scaleIeee Transactions On Pattern Analysis and Machine Intelligence, 2000
- Embedding Gestalt laws in Markov random fieldsIeee Transactions On Pattern Analysis and Machine Intelligence, 1999
- Stochastic Completion Fields: A Neural Model of Illusory Contour Shape and SalienceNeural Computation, 1997
- Multiscale representations of Markov random fieldsIEEE Transactions on Signal Processing, 1993