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Conference papers
Context-Based Probabilistic Scene Interpretation
Abstract : In high-level scene interpretation, it is useful to exploit the evolving probabilistic context for stepwise interpretation decisions. We present a new approach based on a general probabilistic framework and beam search for exploring alternative interpretations. As probabilistic scene models, we propose Bayesian Compositional Hierarchies (BCHs) which provide object-centered representations of compositional hierarchies and efficient evidence-based updates. It is shown that a BCH can be used to represent the evolving context during stepwise scene interpretation and can be combined with low-level image analysis to provide dynamic priors for object classification, improving classification and interpretation. Experimental results are presented illustrating the feasibility of the approach for the interpretation of facade images.
Cited literature [21 references]
https://hal.inria.fr/hal-01054597
Contributor : Hal Ifip <>
Submitted on : Thursday, August 7, 2014 - 3:13:06 PM
Last modification on : Thursday, March 5, 2020 - 5:43:03 PM
Long-term archiving on: : Wednesday, November 26, 2014 - 1:50:33 AM
Contributor : Hal Ifip <>
Submitted on : Thursday, August 7, 2014 - 3:13:06 PM
Last modification on : Thursday, March 5, 2020 - 5:43:03 PM
Long-term archiving on: : Wednesday, November 26, 2014 - 1:50:33 AM
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IFIP-2010-final.pdf
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