We present a data-driven approach to predict the importance of edges and construct a Markov network for image analysis based on statistical models of global and local image features. We also address the coupled problem of predicting the feature weights associated with each edge of a Markov network for evaluation of context. Experimental results indicate that this scene dependent structure construction model eliminates spurious edges and improves performance over fully-connected and neighborhood connected Markov network. © 2010 Springer-Verlag.
CITATION STYLE
Jain, A., Gupta, A., & Davis, L. S. (2010). Learning what and how of contextual models for scene labeling. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6314 LNCS, pp. 199–212). Springer Verlag. https://doi.org/10.1007/978-3-642-15561-1_15
Mendeley helps you to discover research relevant for your work.